ComputationalModellingofPublicPolicy:
ReflectionsonPractice
Nigel Gilbert1, Petra Ahrweiler2, Pete Barbrook-Johnson1, Kavin
PreethiNarasimhan1,HelenWilkinson3
1Department of Sociology, University of Surrey Guildford, GU2 7XH United Kingdom
2InstituteofSociology,JohannesGutenbergUniversityMainz,Jakob-Welder-Weg20,55128Mainz,Germany
3Risk
Solution
s, Dallam Court, Dallam Lane, Warrington, Cheshire, WA2 7LT, United Kingdom
Correspondence should be addressed to [email protected]
Journal of Artificial Societies and Social Simulation 21(1) 14, 2018
Doi: 10.18564/jasss.3669 Url: http://jasss.soc.surrey.ac.uk/21/1/14.html
Received: 11-01-2018 Accepted: 11-01-2018 Published: 31-01-2018
Abstract: Computationalmodelsare increasinglybeingusedtoassist indeveloping, implementingandevalu-
ating public policy. This paper reports on the experience of the authors in designing and using computational
models of public policy (‘policy models’, for short). The paper considers the role of computational models in
policy making, and some of the challenges that need to be overcome if policy models are to make an e�ec-
tive contribution. It suggests that policy models can have an important place in the policy process because
they could allow policy makers to experiment in a virtual world, and have many advantages compared with
randomised control trials and policy pilots. The paper then summarises some general lessons that can be ex-
tractedfromtheauthors’experiencewithpolicymodelling. Thesegeneral lessonsincludetheobservationthat
o�enthemainbenefitofdesigningandusingamodelisthatitprovidesanunderstandingofthepolicydomain,
rather than the numbers it generates; that care needs to be taken that models are designed at an appropriate
level of abstraction; that although appropriate data for calibration and validation may sometimes be in short
supply, modelling is o�en still valuable; that modelling collaboratively and involving a range of stakeholders
from the outset increases the likelihood that the model will be used and will be fit for purpose; that attention
needstobepaidtoe�ectivecommunicationbetweenmodellersandstakeholders;andthatmodellingforpub-
lic policy involves ethical issues that need careful consideration. The paper concludes that policy modelling
will continue to grow in importance as a component of public policy making processes, but if its potential is to
befullyrealised, therewillneedtobeameldingoftheculturesofcomputationalmodellingandpolicymaking.
Keywords: Policy Modelling, Policy Evaluation, Policy Appraisal, Modelling Guidelines, Collaboration, Ethics
Introduction
1.1 Computationalmodelshavebeenusedtoassist indeveloping, implementingandevaluatingpublicpoliciesfor
at least threedecades,but theirpotential remainstobefullyexploited(Johnston&Desouza2015;Anzolaetal.
2017;Barbrook-Johnsonetal.2017). Inthispaper,usingaselectionofexamplesofcomputationalmodelsused
in public policy processes, we (i) consider the roles of models in policy making, (ii) explore .
Computational Modelling of Public PolicyReflections on Prac.docxmccormicknadine86
Computational Modelling of Public Policy:
Reflections on Practice
Nigel Gilbert1, Petra Ahrweiler2, Pete Barbrook-Johnson1, Kavin
Preethi Narasimhan1, Helen Wilkinson3
1Department of Sociology, University of Surrey Guildford, GU2 7XH United Kingdom
2Institute of Sociology, Johannes Gutenberg University Mainz, Jakob-Welder-Weg 20, 55128 Mainz, Germany
3Risk
Solution
s, Dallam Court, Dallam Lane, Warrington, Cheshire, WA2 7LT, United Kingdom
Correspondence should be addressed to [email protected]
Journal of Artificial Societies and Social Simulation 21(1) 14, 2018
Doi: 10.18564/jasss.3669 Url: http://jasss.soc.surrey.ac.uk/21/1/14.html
Received: 11-01-2018 Accepted: 11-01-2018 Published: 31-01-2018
Abstract: Computational models are increasingly being used to assist in developing, implementing and evalu-
ating public policy. This paper reports on the experience of the authors in designing and using computational
models of public policy (‘policy models’, for short). The paper considers the role of computational models in
policy making, and some of the challenges that need to be overcome if policy models are to make an e�ec-
tive contribution. It suggests that policy models can have an important place in the policy process because
they could allow policy makers to experiment in a virtual world, and have many advantages compared with
randomised control trials and policy pilots. The paper then summarises some general lessons that can be ex-
tracted from the authors’ experiencewith policymodelling. These general lessons include the observation that
o�en themain benefit of designing andusing amodel is that it provides anunderstanding of the policy domain,
rather than the numbers it generates; that care needs to be taken that models are designed at an appropriate
level of abstraction; that although appropriate data for calibration and validation may sometimes be in short
supply, modelling is o�en still valuable; that modelling collaboratively and involving a range of stakeholders
from the outset increases the likelihood that the model will be used and will be fit for purpose; that attention
needs to be paid to e�ective communication betweenmodellers and stakeholders; and thatmodelling for pub-
lic policy involves ethical issues that need careful consideration. The paper concludes that policy modelling
will continue to grow in importance as a component of public policy making processes, but if its potential is to
be fully realised, there will need to be amelding of the cultures of computationalmodelling and policymaking.
Keywords: Policy Modelling, Policy Evaluation, Policy Appraisal, Modelling Guidelines, Collaboration, Ethics
Introduction
1.1 Computationalmodels have been used to assist in developing, implementing and evaluating public policies for
at least three decades, but their potential remains to be fully exploited (Johnston & Desouza 2015; Anzola et al.
2017; Barbrook-Johnson et al. 2017). In this paper, using a selection of examples of ...
A virtual environment for formulation of policy packagesAraz Taeihagh
The interdependence and complexity of socio-technical systems and availability of a wide variety of policy measures to address policy problems make the process of policy formulation difficult. In order to formulate sustainable and efficient transport policies, development of new tools and techniques is necessary. One of the approaches gaining ground is policy packaging, which shifts focus from implementation of individual policy measures to implementation of combinations of measures with the aim of increasing efficiency and effectiveness of policy interventions by increasing synergies and reducing potential contradictions among policy measures. In this paper, we describe the development of a virtual environment for the exploration and analysis of different configurations of policy measures in order to build policy packages. By developing systematic approaches it is possible to examine more alternatives at a greater depth, decrease the time required for the overall analysis, provide real-time assessment and feedback on the effect of changes in the configurations, and ultimately form more effective policies. The results from this research demonstrate the usefulness of computational approaches in addressing the complexity inherent in the formulation of policy packages. This new approach has been applied to the formulation of policies to advance sustainable transportation.
Two important challenges in policy design are better understanding of the design
space and consideration of the temporal factors. Moreover, in recent years it has been
demonstrated that understanding the complex interactions of policy measures can play an
important role in policy design and analysis. In this paper, the advances made in conceptualization
and application of networks to policy design in the past decade are highlighted.
Specifically, the use of a network-centric policy design approach in better
understanding the design space and temporal consequences of design choices are presented.
Network-centric policy design approach has been used in classification, visualization,
and analysis of the relations among policy measures as well as ranking of policy
measures using their internal properties and interactions, and conducting sensitivity
analysis using Monte Carlo simulations. Furthermore, through use of a decision support
system, network-centric approach facilitates ranking, visualization, and selection of policies
using different sets of criteria, and exploring the potential for compromise in policy
formulation. The advantage of the network-centric approach is providing the ability to go
beyond visualizations and analysis of policies and piecemeal use of network concepts as a
tool for different policy design tasks to moving to a more integrated bottom–up approach to
design. Furthermore, the computational advantages of the network-centric policy design in
considering temporal factors such as policy sequencing and addressing issues such as
layering, drift, policy failure, and delay are presented. Finally, some of the current challenges
of network-centric design are discussed, and some potential avenues of exploration
in policy design through use of computational methodologies, as well as possible integration
with approaches from other disciplines, are highlighted.
This document discusses ethics in strategic and tactical public relations management and how it affects the United States. It begins by defining public relations and explaining that strategic management uses a dialogical approach in studies, while tactical management uses a monological approach. It then analyzes case studies and the positive and negative aspects of both methods. The document discusses how Johnson & Johnson's strategic planning helped it recover from a Tylenol crisis. It concludes that strategic management is more ethical as it allows for more diverse groups to be represented in media studies. However, it can be improved by incorporating more social network analysis. Overall, the document argues strategic public relations management has a more positive impact on society than tactical management.
Crowdsourcing: a new tool for policy-making?Araz Taeihagh
Crowdsourcing is rapidly evolving and applied in situations where ideas, labour, opinion or expertise of large groups of people are used. Crowdsourcing is now used in various policy-making initiatives; however, this use has usually focused on open collaboration platforms and specific stages of the policy process, such as agenda-setting and policy evaluations. Other forms of crowdsourcing have been neglected in policymaking, with a few exceptions. This article examines crowdsourcing as a tool for policymaking, and explores the nuances of the technology and its use and implications for different stages of the policy process. The article addresses questions surrounding the role of crowdsourcing and whether it can be considered as a policy tool or as a technological enabler and investigates the current trends and future directions of crowdsourcing.
Computational Modelling of Public PolicyReflections on Prac.docxmccormicknadine86
Computational Modelling of Public Policy:
Reflections on Practice
Nigel Gilbert1, Petra Ahrweiler2, Pete Barbrook-Johnson1, Kavin
Preethi Narasimhan1, Helen Wilkinson3
1Department of Sociology, University of Surrey Guildford, GU2 7XH United Kingdom
2Institute of Sociology, Johannes Gutenberg University Mainz, Jakob-Welder-Weg 20, 55128 Mainz, Germany
3Risk
Solution
s, Dallam Court, Dallam Lane, Warrington, Cheshire, WA2 7LT, United Kingdom
Correspondence should be addressed to [email protected]
Journal of Artificial Societies and Social Simulation 21(1) 14, 2018
Doi: 10.18564/jasss.3669 Url: http://jasss.soc.surrey.ac.uk/21/1/14.html
Received: 11-01-2018 Accepted: 11-01-2018 Published: 31-01-2018
Abstract: Computational models are increasingly being used to assist in developing, implementing and evalu-
ating public policy. This paper reports on the experience of the authors in designing and using computational
models of public policy (‘policy models’, for short). The paper considers the role of computational models in
policy making, and some of the challenges that need to be overcome if policy models are to make an e�ec-
tive contribution. It suggests that policy models can have an important place in the policy process because
they could allow policy makers to experiment in a virtual world, and have many advantages compared with
randomised control trials and policy pilots. The paper then summarises some general lessons that can be ex-
tracted from the authors’ experiencewith policymodelling. These general lessons include the observation that
o�en themain benefit of designing andusing amodel is that it provides anunderstanding of the policy domain,
rather than the numbers it generates; that care needs to be taken that models are designed at an appropriate
level of abstraction; that although appropriate data for calibration and validation may sometimes be in short
supply, modelling is o�en still valuable; that modelling collaboratively and involving a range of stakeholders
from the outset increases the likelihood that the model will be used and will be fit for purpose; that attention
needs to be paid to e�ective communication betweenmodellers and stakeholders; and thatmodelling for pub-
lic policy involves ethical issues that need careful consideration. The paper concludes that policy modelling
will continue to grow in importance as a component of public policy making processes, but if its potential is to
be fully realised, there will need to be amelding of the cultures of computationalmodelling and policymaking.
Keywords: Policy Modelling, Policy Evaluation, Policy Appraisal, Modelling Guidelines, Collaboration, Ethics
Introduction
1.1 Computationalmodels have been used to assist in developing, implementing and evaluating public policies for
at least three decades, but their potential remains to be fully exploited (Johnston & Desouza 2015; Anzola et al.
2017; Barbrook-Johnson et al. 2017). In this paper, using a selection of examples of ...
A virtual environment for formulation of policy packagesAraz Taeihagh
The interdependence and complexity of socio-technical systems and availability of a wide variety of policy measures to address policy problems make the process of policy formulation difficult. In order to formulate sustainable and efficient transport policies, development of new tools and techniques is necessary. One of the approaches gaining ground is policy packaging, which shifts focus from implementation of individual policy measures to implementation of combinations of measures with the aim of increasing efficiency and effectiveness of policy interventions by increasing synergies and reducing potential contradictions among policy measures. In this paper, we describe the development of a virtual environment for the exploration and analysis of different configurations of policy measures in order to build policy packages. By developing systematic approaches it is possible to examine more alternatives at a greater depth, decrease the time required for the overall analysis, provide real-time assessment and feedback on the effect of changes in the configurations, and ultimately form more effective policies. The results from this research demonstrate the usefulness of computational approaches in addressing the complexity inherent in the formulation of policy packages. This new approach has been applied to the formulation of policies to advance sustainable transportation.
Two important challenges in policy design are better understanding of the design
space and consideration of the temporal factors. Moreover, in recent years it has been
demonstrated that understanding the complex interactions of policy measures can play an
important role in policy design and analysis. In this paper, the advances made in conceptualization
and application of networks to policy design in the past decade are highlighted.
Specifically, the use of a network-centric policy design approach in better
understanding the design space and temporal consequences of design choices are presented.
Network-centric policy design approach has been used in classification, visualization,
and analysis of the relations among policy measures as well as ranking of policy
measures using their internal properties and interactions, and conducting sensitivity
analysis using Monte Carlo simulations. Furthermore, through use of a decision support
system, network-centric approach facilitates ranking, visualization, and selection of policies
using different sets of criteria, and exploring the potential for compromise in policy
formulation. The advantage of the network-centric approach is providing the ability to go
beyond visualizations and analysis of policies and piecemeal use of network concepts as a
tool for different policy design tasks to moving to a more integrated bottom–up approach to
design. Furthermore, the computational advantages of the network-centric policy design in
considering temporal factors such as policy sequencing and addressing issues such as
layering, drift, policy failure, and delay are presented. Finally, some of the current challenges
of network-centric design are discussed, and some potential avenues of exploration
in policy design through use of computational methodologies, as well as possible integration
with approaches from other disciplines, are highlighted.
This document discusses ethics in strategic and tactical public relations management and how it affects the United States. It begins by defining public relations and explaining that strategic management uses a dialogical approach in studies, while tactical management uses a monological approach. It then analyzes case studies and the positive and negative aspects of both methods. The document discusses how Johnson & Johnson's strategic planning helped it recover from a Tylenol crisis. It concludes that strategic management is more ethical as it allows for more diverse groups to be represented in media studies. However, it can be improved by incorporating more social network analysis. Overall, the document argues strategic public relations management has a more positive impact on society than tactical management.
Crowdsourcing: a new tool for policy-making?Araz Taeihagh
Crowdsourcing is rapidly evolving and applied in situations where ideas, labour, opinion or expertise of large groups of people are used. Crowdsourcing is now used in various policy-making initiatives; however, this use has usually focused on open collaboration platforms and specific stages of the policy process, such as agenda-setting and policy evaluations. Other forms of crowdsourcing have been neglected in policymaking, with a few exceptions. This article examines crowdsourcing as a tool for policymaking, and explores the nuances of the technology and its use and implications for different stages of the policy process. The article addresses questions surrounding the role of crowdsourcing and whether it can be considered as a policy tool or as a technological enabler and investigates the current trends and future directions of crowdsourcing.
A Critical Account of Policy Implementation Theories: Status and ReconsiderationNurwant0
This document summarizes the evolution of policy implementation theories over three generations of research. The first generation, led by Pressman and Wildavsky in the 1970s, identified the problem of uncertain relationships between policies and implemented programs. The second generation in the 1980s-1990s developed analytical frameworks using top-down and bottom-up perspectives. The third generation beginning in the 1990s aimed to build explicit implementation theories through comparative case studies and statistical research designs. Key debates discussed include the merits of top-down vs bottom-up approaches and the lack of comprehensive synthesis across studies. The document also notes issues in applying policy implementation theories across different geographic and sectoral contexts.
Which policy first? A network-centric approach for the analysis and ranking o...Araz Taeihagh
In addressing various policy problems, deciding which policy measure to start with given the range of measures available is challenging and essentially involves a process of ranking the alternatives, commonly done using multicriteria decision analysis (MCDA) techniques. In this paper a new methodology for analysis and ranking of policy measures is introduced which combines network analysis and MCDA tools. This methodology not only considers the internal properties of the measures but also their interactions with other potential measures. Consideration of such interactions provides additional insights into the process of policy formulation and can help domain experts and policy makers to better assess the policy measures and to understand the complexities involved. This new methodology is applied in this paper to the formulation of a policy to increase walking and cycling.
The document discusses different theories on how research informs policymaking processes. The traditional linear model of research directly leading to policy changes is now recognized as oversimplified, as policymaking involves complex political contexts and competing demands. A more realistic model sees policymaking as an iterative process where research plays a minimal role, with policymakers using information in the context of their own agendas. A third approach focuses on interactions between actors and discourse. The document also notes that researchers need to identify which part of the policy process to inform, as this impacts how findings are presented and communicated. It further discusses differences in what researchers and policymakers consider evidence.
Experiments on Crowdsourcing Policy Assessment - Oxford IPP 2014Araz Taeihagh
This document summarizes an experiment that tested whether non-expert crowds can assess policy measures as well as experts. Researchers conducted two experiments using crowdsourced labor markets: one with Dutch participants and one with global participants. Both crowds evaluated 96 climate change adaptation policy measures on criteria like importance and urgency. The measures were previously assessed by Dutch experts. Results were analyzed to see how non-expert crowd assessments compared to expert assessments and whether geography impacted non-expert performance. The goal was to determine if crowds could be useful for policy design by evaluating policy alternatives.
This document discusses the role of theory in public relations. It summarizes the debate around different models of public relations proposed by scholars like Grunig and Hunt. While Grunig's two-way symmetrical model was once seen as ideal, others have critiqued aspects of it. The document also analyzes a case study of Hamleys toy store bringing live animals into its store, and the public backlash it received, demonstrating the importance of theory for ethical public relations practice in a global, digital environment.
1. The document discusses the potential uses of social media analytics in local government. It identifies four main purposes: communication, public relations, customer services, and public consultation/engagement.
2. It details a research project with two UK city councils that included a workshop introducing social media analytics tools and interviews. The workshop aimed to demonstrate tools and generate reflection on their value.
3. Interview findings suggested analytics could provide insights supplementing existing knowledge of public networks and discussions. Tools were seen as potentially valuable across different council departments.
MDRC Working Papers on Research Methodology In.docxARIV4
The New Chance demonstration project provided educational, social, and employment supports to teenage welfare recipients who had dropped out of high school. While quantitative data from the project found high dropout rates and low service participation, qualitative research in the form of 50 one-on-one interviews with program participants aimed to understand these issues from the participants' perspectives. The interviews explored how life experiences and contexts influenced participation in the program and later success. The qualitative research provided a richer understanding of the quantitative findings and participants' behaviors.
This document summarizes a research paper that empirically assesses the impact of different recommender systems on content diversity. It proposes new metrics to measure diversity across multiple dimensions, such as topic plurality and genre variety. The study finds that recommender systems based on user histories can substantially increase topic diversity within recommendations compared to only considering users' past selections. All the recommendation approaches tested led to recommendation sets that were as diverse as those chosen by human editors. The paper contributes new methods for more accurately evaluating diversity in algorithmic recommendations.
rsos.royalsocietypublishing.orgReviewCite this article .docxhealdkathaleen
rsos.royalsocietypublishing.org
Review
Cite this article: Calder M etal. 2018
Computational modelling for
decision-making: where, why, what, who and
how. R.Soc.opensci. 5: 172096.
http://dx.doi.org/10.1098/rsos.172096
Received: 6 December 2017
Accepted: 10 May 2018
Subject Category:
Computer science
Subject Areas:
computer modelling and
simulation/mathematical modelling
Keywords:
modelling, decision-making, data,
uncertainty, complexity, communication
Author for correspondence:
Muffy Calder
e-mail: [email protected]
Computational modelling
for decision-making: where,
why, what, who and how
Muffy Calder1, Claire Craig2, Dave Culley3, Richard de
Cani4, Christl A. Donnelly5, Rowan Douglas6, Bruce
Edmonds7, Jonathon Gascoigne6, Nigel Gilbert8,
Caroline Hargrove9, Derwen Hinds10, David C. Lane11,
Dervilla Mitchell4, Giles Pavey12, David Robertson13,
Bridget Rosewell14, Spencer Sherwin15, Mark
Walport16 and Alan Wilson17
1School of Computing Science, University of Glasgow, Glasgow, UK
2The Royal Society, London, UK
3Improbable, London, UK
4Arup, London, UK
5MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease
Epidemiology, Imperial College London, London, UK
6Willis Towers Watson, London, UK
7Centre for Policy Modelling, Manchester Metropolitan University, Manchester, UK
8Centre for Research in Social Simulation, University of Surrey, Guildford, UK
9McLaren Applied Technologies, Woking, UK
10National Cyber Security Centre, UK
11Henley Business School, University of Reading, Reading, UK
12Consultant, UK
13School of Informatics, University of Edinburgh, Edinburgh, UK
14Volterra Partners, London, UK
15Department of Aeronautics, Imperial College London, London, UK
16UK Research and Innovation, London, UK
17The Alan Turing Institute, London, UK
BE, 0000-0002-3903-2507
In order to deal with an increasingly complex world, we
need ever more sophisticated computational models that can
help us make decisions wisely and understand the potential
consequences of choices. But creating a model requires far
more than just raw data and technical skills: it requires a
2018 The Authors. Published by the Royal Society under the terms of the Creative Commons
Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted
use, provided the original author and source are credited.
http://crossmark.crossref.org/dialog/?doi=10.1098/rsos.172096&domain=pdf&date_stamp=2018-06-20
mailto:[email protected]
http://orcid.org/0000-0002-3903-2507
2
rsos.royalsocietypublishing.org
R.Soc.open
sci.5:172096
.................................................
close collaboration between model commissioners, developers, users and reviewers. Good modelling
requires its users and commissioners to understand more about the whole process, including the
different kinds of purpose a model can have and the different technical bases. This paper offers a
guide to the process of commissioning, developing and deploying mo ...
Public Policy Analysis (PPA)PresentationBYDr. Henry Akwo E.docxamrit47
Public Policy Analysis (PPA)
Presentation
BY
Dr. Henry Akwo Elonge
1
PPA
Introduction to Public Policy Analysis
What is Public Policy: Public policy is concerned with what governments choose to do, why they do it and what difference it makes in society.
Public policies may regulate, distribute and even extract resources from members of the society
Policy Analysis attempts to describe, analyze and explain public policy. It is the description and explanation of the causes and consequences of governmental activities
2
PPA
Specifically, Policy Analysis involves:
A primary concern with explanation rather than prescription
A rigorous search for the causes and consequences of public policies
An effort to develop and test general propositions about the causes of public policies and to accumulate reliable research findings
3
PPA
Limitations of Policy Analysis:
The limits of government power. What governments can/cannot do
Public dis-agreements over the nature of problems in society
Subjectivity in analysis and interpretation
Limitations on research design and methodologies
Complexity of human problems/ Human diversity
“Today’s solutions constitute tomorrow’s problems”
4
PPA
Expert Definitions of Public Policy:
David Easton( The Political System – 1953) defines public policy as” the authoritative allocation of values for the whole of society>”
Harold Lasswell and Abraham Kaplan (Power and Society – 1970) define public policy as a projected program of goals, values and practices
Carl J. Friedrich ( Man and His Government – 1963) stresses that the policy concept should have a goal, an objective and a purpose.
Charles Jones ( Introduction to the Study of Public Policy – 1977) breaks down the notion of public policy into various components and parts and measurable impacts
5
PPA
According to Weimer and Vining, policy analysis is client-oriented advice relevant to public decisions and informed by social values.
Michael Kraft and Scott Furlong indicate that analysis means deconstructing an object of study, that is breaking it down into its basic elements to understand it better. It is the examination of components of public policy, the policy process or both.
6
PPA
Utility of models in Policy Analysis
Models are simplified representations of reality or some aspect of the real world; It may be an actual physical representation or a diagram or road map Models
Simplify and clarify our thinking about politics and public policy
Identify important aspects of policy problems
Help us communicate with each other by focusing on essential features of political life;
Direct our efforts to understand public policy better
Suggest explanations for public policy and predict its consequences
7
PPA
Models are mainly abstractions of the real life. Are they Useful in policy analysis?
Can models order and Simplify reality. Yes they can. But too much simplification may also lead to a false sense of the reality. Models are only ...
Social policy analysis uses various methods to evaluate policies and their impact. Policy analysts conduct needs assessments, evaluate outcomes, and use case studies and content analysis. The goal is to understand problems policies aim to address, determine if objectives are met, and identify unintended consequences. Analysts may also use grounded theory to uncover themes in policies and develop theories about values and ideologies underlying them. Overall, social policy analysis provides a way to critically examine social problems, policies, and services to promote social justice and improve people's quality of life.
The document discusses different theories of how evidence informs policy processes. The traditional linear model of research directly leading to policy changes is now recognized as too simplistic, as it ignores political contexts and competing demands. A more realistic iterative model sees policymakers using research to expand options rather than passively receiving information. A third approach focuses on interactions between actors and networks. It is important for researchers to identify which part of the policy process to inform and use appropriate communication tactics and timing. Policymakers and researchers often have differing views of what constitutes evidence.
The document discusses different theories of how evidence informs policy processes. The traditional linear model of research directly leading to policy changes is now recognized as oversimplified, as it ignores political contexts and competing demands. A more realistic iterative model sees policymakers using research to expand options rather than passively receiving information. A third approach focuses on interactions between actors and networks. The document also notes that identifying the target policy process stage and understanding differing notions of evidence between researchers and policymakers are important practical considerations for researchers seeking to inform policy.
“Public Policy Analysis” involves in the evaluation of issues of public importance with objective of providing facts and statistics about extent and impact of different policies of Government. Nowadays, public policy analysis is undertaken by scholars from different applied physical and biological sciences (e.g. technology assessments, environmental impact studies, seismic risk analyses, etc.). Presently, the focus is on public policy analysis as it is conducted within the social and behavioural sciences, mainly Political Science, Sociology and Economics. Generally, the public policy addresses real or sensed problems, so the public policy analysis is mostly devoted to defining or clarifying the problems and assessing the needs. Main objective of public policy analysis is to assess the degree to which policies are meeting their aims. Policy analysis plays an important role to define and outline the aims of a proposed policy, and also has role to identify the similarities and differences in expected outcomes and estimated costs with competing the alternative policies. Several public policies are formulated to solve both the current and future problems, and so the policy analysis attempts to forecast future requirements based on present concomitant with the past conditions. A large number of works in the field of public policy analysis involves for the development of the conceptual schemes or typologies which help to sort out different types of policies, or analyses of policies. Many literatures on public policy analysis, and especially on impact evaluation are chiefly methodological in character; indeed, many recent innovations in research procedure have been developed by research scholars working on applied problems. Many texts in ‘evaluation research’ recommend an assessment of the ‘evaluability’ of the programme prior to initiate the evaluation itself. ‘Implementation analysis’ is an essential component of all capable policy evaluations. ‘Utilisation’ is an ongoing problem in the field of evaluation research. Evaluation results affect the public policy by serving as the impetus for public discourse and debate which form social policy, rather than through extensive programme termination or reform.
Policy report final by Merlinda D Gorriceta, Joy S Sumortin, Derna F BancienDer Na Fuente Bella
The document discusses various models and methodologies used in policy analysis, including rational, incremental, group, elite, and systems models. It also covers qualitative and quantitative research methods used in policy analysis like case studies, surveys, and statistical analysis. The document provides examples of different types of policy analysis, such as ethical, strategic, and operational policy components.
Crowdsourcing the Policy Cycle - Collective Intelligence 2014 Araz Taeihagh ...Araz Taeihagh
Crowdsourcing is beginning to be used for policymaking. The “wisdom of crowds” [Surowiecki 2005], and crowdsourcing [Brabham 2008], are seen as new avenues that can shape all kinds of policy, from transportation policy [Nash 2009] to urban planning [Seltzer and Mahmoudi 2013], to climate policy. In general, many have high expectations for positive outcomes with crowdsourcing, and based on both anecdotal and empirical evidence, some of these expectations seem justified [Majchrzak and Malhotra 2013]. Yet, to our knowledge, research has yet to emerge that unpacks the different forms of crowdsourcing in light of each stage of the well-established policy cycle. This work addresses this research gap, and in doing so brings increased nuance to the application of crowdsourcing techniques for policymaking.
Why social policy needs more than the behavioural economics bandwagonTNS
1. Behavioural economics provides useful insights but is not a "magic bullet" solution for changing human behaviour. Lasting change requires a holistic approach that considers psychological, social, cultural, and deliberative factors beyond just unconscious triggers.
2. An integrated approach is needed that combines insights from behavioural economics with traditional behavioural sciences. Sustainable behaviour change stems from addressing most or all influences in a "behavioural web" that includes costs/benefits, efficacy, habits, heuristics, morality, and legitimacy.
3. Both traditional research methods and newer techniques attuned to unconscious influences are important for fully understanding human behaviour. A balanced approach using diverse methods can provide insights needed for effective social policy
Explain the six step model for public policy by SYED SALMAN JALAL KAKA KHELSalman Kaka Khel
The six step model for public policy formation prescribed by Patton and Sawicki (1986) includes: 1) Verify and define the problem, 2) Establish evaluation criteria, 3) Identify alternative policies, 4) Evaluate alternative policies, 5) Select among alternative policies, and 6) Monitor policy outcomes. However, the model has limitations as public policy problems are complex, models provide frameworks not concrete methods, and perfect adherence to a model could still produce a flawed policy.
r The Impact of Social Policy Pranab Chatterjee an.docxaudeleypearl
r
The Impact of
Social Policy
Pranab Chatterjee and Diwakar Vadapalli
'"I·-\ere is increasing recognition today that social policies and programs
should be carefully evaluated to determine whether they do, in fact,
meet their stated objectives. Althongh it has often been assumed that social
policies have a positive impact, this assumption has been called into question
by many critics of government social programs. This chapter discusses the
ways in which the impact of social policies can be assessed. It describes the
principles and techniques used in different types of evaluation. Although
evaluation research has become increasingly sophisticated, values and ideolo
gies continue to play an important role in deciding which policy approaches
work best.
___________ The logic of Bmpact Analysis
Rossi and Freeman (1985, 1993) and Rossi, Lipsey, and Freeman (2004)
observe that there are four phases of social policy evaluation. These are
needs assessment, selection of a program to respond to needs, impact evalu
ation, and cost-benefit analysis. Upon outlining the four phases of evalua
tion, they discuss many experimental, quasi-experimental, and time-series
designs that can be used for program evaluation. Mohr (1995) singled out
the idea of impact evaluation and called it an attempt to isolate the direct
effects of a policy (or, more precisely, a program derived from a policy) apart
from any confounding environmental effects. Earlier, Suchman (1967) sng
gested tbat a program is a form of social experiment, and any evaluation of
it leads to the conclusion tbat the program does or does not produce given
social ends. Following Suchrnan's ideas, Riecken and Baruch (1974) listed
ways of evaluating the impact of social experiments, many of which can be
construed as preludes to new forms of social policy. Schalock (2001), using
83
84
I
THE NATURE OF SOCIAL POLICY
T
these contributions, defined outcome-based evaluation as evaluation that
uses valued and objective person- and organization-referenced outcon1es to
analyze a program's effectiveness, impact, or efficiency. Snchman (1967), in
his earlier work, had stated that, if any one program does not produce given
social ends, one should conclude that it is a case of program failure.
However, if it seems that a substantial number of programs, all similar
in nature, do not produce given ends, then it indicates a case of theory fail
ure. In other words, the theory that generated the programs (as interven
tions to bring about a change) has been developed on faulty premises.
The groundwork of Rossi and Suchman on impact analysis (both of
social programs and of the parent policies or theories on which they rest) is
based on the assumption that quantitative analysis and multivariate design
will produce knowledge about the impact of social policies and programs.
Ask a typical policy analyst, academic, or program-administrator about the
impact of social ...
Concept of collection. Assume that An agency has focused its sys.docxpatricke8
C
oncept of collection
. Assume that An agency has focused its system development and critical infrastructure data collection efforts on separate engineering management systems for different types of assets and is working on the integration of these systems. In this case, the agency focused on the data collection for two types of assets: water treatment and natural gas delivery management facilities.
Please identify what type of critical infrastructure data collection is needed for pavement and storm water management facilities.
.
Concept of AestheticsOVERVIEWAesthetics is defined as an appre.docxpatricke8
Concept of Aesthetics
OVERVIEW
Aesthetics is defined as an appreciation for beauty and a feeling of wonder. Teachers can help
develop children’s aesthetic senses by involving them in the arts through introduction to works
of art, music, dance, and literature. Children’s aesthetic sensibilities are enhanced by allowing
them to explore their environment in a manner that encourages divergent thinking. In discussing
art with children, basic elements such as line, color, form, space, and design are all appropriate.
Teachers can create aesthetic opportunities in the classroom by providing children with
materials, supplies, room décor, objects, books, visiting artists, and varied activities to stimulate
their aesthetic sense.
There are three basic ways to provide young children with developmentally appropriate
aesthetic experiences in the early childhood program:
Provide many opportunities to create art.
Provide many opportunities to look at and talk about art.
Help children become aware of art in their everyday lives.
Developing children’s aesthetic sensitivity is important because it improves the quality of their
learning and encourages the creative process.
KEY TERMS
aesthetic development
—
Teaching young children to appreciate art through everyday
experiences, play, and conversations
aesthetic experiences
—
Experiences involving an appreciation of the beauty of nature, the
rhythm and imagery of music or poetry, or the qualities of works of art.
aesthetic learning
—
Joining what one thinks with what one feels
Aesthetics Movement
—
Movement in the world beginning in early 1800 and lasting the
decade, emphasizing the “science of the beautiful” or the “philosophy of taste.”
aesthetics
—
An appreciation for beauty and a feeling of wonder. It is a sensibility that uses the
imagination as well as the five senses.
aesthetic sense —
One’s own specific taste or preference.
art appreciation
— Seeing and appreciating good artwork; learning to look at and learning to
create visual arts
art elements
—
Basic factors of art that can be used to describe art. These elements include
color, line, form or shape, space, and design.
balance —
The principle of design that deals with visual weight in a work of art
color/hue —
The color name
pattern —
When a particular shape, color, or motif is repeated in a rhythmic way
intensity —
The varied color when a hue’s complementary color, the color opposite it on the
color wheel, is added to the original color
language of art —
Expansion of the language of the early childhood classroom.
The words of
the language are the elements of art.
line —
A continuous mark on a surface
multicultural aesthetics —
A worldview of art which honors heritage, community, and tradition
multimedia artwork —
Integration of art such as walk-in sculpture environments; mixes of live
dance and films; and art exhibitions with drama, where actors move into the audience to engage
in the drama
primary colors —
Red, blue, and yellow.
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Computational modelling for
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how. R.Soc.opensci. 5: 172096.
http://dx.doi.org/10.1098/rsos.172096
Received: 6 December 2017
Accepted: 10 May 2018
Subject Category:
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Subject Areas:
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Computational modelling
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why, what, who and how
Muffy Calder1, Claire Craig2, Dave Culley3, Richard de
Cani4, Christl A. Donnelly5, Rowan Douglas6, Bruce
Edmonds7, Jonathon Gascoigne6, Nigel Gilbert8,
Caroline Hargrove9, Derwen Hinds10, David C. Lane11,
Dervilla Mitchell4, Giles Pavey12, David Robertson13,
Bridget Rosewell14, Spencer Sherwin15, Mark
Walport16 and Alan Wilson17
1School of Computing Science, University of Glasgow, Glasgow, UK
2The Royal Society, London, UK
3Improbable, London, UK
4Arup, London, UK
5MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease
Epidemiology, Imperial College London, London, UK
6Willis Towers Watson, London, UK
7Centre for Policy Modelling, Manchester Metropolitan University, Manchester, UK
8Centre for Research in Social Simulation, University of Surrey, Guildford, UK
9McLaren Applied Technologies, Woking, UK
10National Cyber Security Centre, UK
11Henley Business School, University of Reading, Reading, UK
12Consultant, UK
13School of Informatics, University of Edinburgh, Edinburgh, UK
14Volterra Partners, London, UK
15Department of Aeronautics, Imperial College London, London, UK
16UK Research and Innovation, London, UK
17The Alan Turing Institute, London, UK
BE, 0000-0002-3903-2507
In order to deal with an increasingly complex world, we
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2018 The Authors. Published by the Royal Society under the terms of the Creative Commons
Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted
use, provided the original author and source are credited.
http://crossmark.crossref.org/dialog/?doi=10.1098/rsos.172096&domain=pdf&date_stamp=2018-06-20
mailto:[email protected]
http://orcid.org/0000-0002-3903-2507
2
rsos.royalsocietypublishing.org
R.Soc.open
sci.5:172096
.................................................
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Public Policy Analysis (PPA)
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PPA
Introduction to Public Policy Analysis
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PPA
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3
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The Impact of
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Pranab Chatterjee and Diwakar Vadapalli
'"I·-\ere is increasing recognition today that social policies and programs
should be carefully evaluated to determine whether they do, in fact,
meet their stated objectives. Althongh it has often been assumed that social
policies have a positive impact, this assumption has been called into question
by many critics of government social programs. This chapter discusses the
ways in which the impact of social policies can be assessed. It describes the
principles and techniques used in different types of evaluation. Although
evaluation research has become increasingly sophisticated, values and ideolo
gies continue to play an important role in deciding which policy approaches
work best.
___________ The logic of Bmpact Analysis
Rossi and Freeman (1985, 1993) and Rossi, Lipsey, and Freeman (2004)
observe that there are four phases of social policy evaluation. These are
needs assessment, selection of a program to respond to needs, impact evalu
ation, and cost-benefit analysis. Upon outlining the four phases of evalua
tion, they discuss many experimental, quasi-experimental, and time-series
designs that can be used for program evaluation. Mohr (1995) singled out
the idea of impact evaluation and called it an attempt to isolate the direct
effects of a policy (or, more precisely, a program derived from a policy) apart
from any confounding environmental effects. Earlier, Suchman (1967) sng
gested tbat a program is a form of social experiment, and any evaluation of
it leads to the conclusion tbat the program does or does not produce given
social ends. Following Suchrnan's ideas, Riecken and Baruch (1974) listed
ways of evaluating the impact of social experiments, many of which can be
construed as preludes to new forms of social policy. Schalock (2001), using
83
84
I
THE NATURE OF SOCIAL POLICY
T
these contributions, defined outcome-based evaluation as evaluation that
uses valued and objective person- and organization-referenced outcon1es to
analyze a program's effectiveness, impact, or efficiency. Snchman (1967), in
his earlier work, had stated that, if any one program does not produce given
social ends, one should conclude that it is a case of program failure.
However, if it seems that a substantial number of programs, all similar
in nature, do not produce given ends, then it indicates a case of theory fail
ure. In other words, the theory that generated the programs (as interven
tions to bring about a change) has been developed on faulty premises.
The groundwork of Rossi and Suchman on impact analysis (both of
social programs and of the parent policies or theories on which they rest) is
based on the assumption that quantitative analysis and multivariate design
will produce knowledge about the impact of social policies and programs.
Ask a typical policy analyst, academic, or program-administrator about the
impact of social ...
Similar to ComputationalModellingofPublicPolicyReflectionsonPractice.docx (20)
Concept of collection. Assume that An agency has focused its sys.docxpatricke8
C
oncept of collection
. Assume that An agency has focused its system development and critical infrastructure data collection efforts on separate engineering management systems for different types of assets and is working on the integration of these systems. In this case, the agency focused on the data collection for two types of assets: water treatment and natural gas delivery management facilities.
Please identify what type of critical infrastructure data collection is needed for pavement and storm water management facilities.
.
Concept of AestheticsOVERVIEWAesthetics is defined as an appre.docxpatricke8
Concept of Aesthetics
OVERVIEW
Aesthetics is defined as an appreciation for beauty and a feeling of wonder. Teachers can help
develop children’s aesthetic senses by involving them in the arts through introduction to works
of art, music, dance, and literature. Children’s aesthetic sensibilities are enhanced by allowing
them to explore their environment in a manner that encourages divergent thinking. In discussing
art with children, basic elements such as line, color, form, space, and design are all appropriate.
Teachers can create aesthetic opportunities in the classroom by providing children with
materials, supplies, room décor, objects, books, visiting artists, and varied activities to stimulate
their aesthetic sense.
There are three basic ways to provide young children with developmentally appropriate
aesthetic experiences in the early childhood program:
Provide many opportunities to create art.
Provide many opportunities to look at and talk about art.
Help children become aware of art in their everyday lives.
Developing children’s aesthetic sensitivity is important because it improves the quality of their
learning and encourages the creative process.
KEY TERMS
aesthetic development
—
Teaching young children to appreciate art through everyday
experiences, play, and conversations
aesthetic experiences
—
Experiences involving an appreciation of the beauty of nature, the
rhythm and imagery of music or poetry, or the qualities of works of art.
aesthetic learning
—
Joining what one thinks with what one feels
Aesthetics Movement
—
Movement in the world beginning in early 1800 and lasting the
decade, emphasizing the “science of the beautiful” or the “philosophy of taste.”
aesthetics
—
An appreciation for beauty and a feeling of wonder. It is a sensibility that uses the
imagination as well as the five senses.
aesthetic sense —
One’s own specific taste or preference.
art appreciation
— Seeing and appreciating good artwork; learning to look at and learning to
create visual arts
art elements
—
Basic factors of art that can be used to describe art. These elements include
color, line, form or shape, space, and design.
balance —
The principle of design that deals with visual weight in a work of art
color/hue —
The color name
pattern —
When a particular shape, color, or motif is repeated in a rhythmic way
intensity —
The varied color when a hue’s complementary color, the color opposite it on the
color wheel, is added to the original color
language of art —
Expansion of the language of the early childhood classroom.
The words of
the language are the elements of art.
line —
A continuous mark on a surface
multicultural aesthetics —
A worldview of art which honors heritage, community, and tradition
multimedia artwork —
Integration of art such as walk-in sculpture environments; mixes of live
dance and films; and art exhibitions with drama, where actors move into the audience to engage
in the drama
primary colors —
Red, blue, and yellow.
Concept mapping, mind mapping and argumentmapping what are .docxpatricke8
Concept mapping, mind mapping and argument
mapping: what are the differences and do they matter?
Martin Davies
Published online: 27 November 2010
� Springer Science+Business Media B.V. 2010
Abstract In recent years, academics and educators have begun to use software map-
ping tools for a number of education-related purposes. Typically, the tools are used to
help impart critical and analytical skills to students, to enable students to see rela-
tionships between concepts, and also as a method of assessment. The common feature
of all these tools is the use of diagrammatic relationships of various kinds in preference
to written or verbal descriptions. Pictures and structured diagrams are thought to be
more comprehensible than just words, and a clearer way to illustrate understanding of
complex topics. Variants of these tools are available under different names: ‘‘concept
mapping’’, ‘‘mind mapping’’ and ‘‘argument mapping’’. Sometimes these terms are used
synonymously. However, as this paper will demonstrate, there are clear differences in
each of these mapping tools. This paper offers an outline of the various types of tool
available and their advantages and disadvantages. It argues that the choice of mapping
tool largely depends on the purpose or aim for which the tool is used and that the tools
may well be converging to offer educators as yet unrealised and potentially comple-
mentary functions.
Keywords Concept mapping � Mind mapping � Computer-aided argument mapping �
Critical thinking � Argument � Inference-making � Knowledge mapping
Introduction
In the past 5–10 years, a variety of software packages have been developed that enable the
visual display of information, concepts and relations between ideas. These mapping tools
take a variety of names including: ‘‘concept mapping’’, ‘‘mind mapping’’ or ‘‘argument
mapping’’. The potential of these tools for educational purposes is only now starting to be
realised.
M. Davies (&)
University of Melbourne, Parkville, VIC, Australia
e-mail: [email protected]
123
High Educ (2011) 62:279–301
DOI 10.1007/s10734-010-9387-6
The idea of displaying complex information visually is, of course, quite old. Flow
charts, for example, were developed in 1972 (Nassi and Shneiderman 1973) pie charts and
other visual formats go back much earlier (Tufte 1983). More recently, visual displays
have been used to simplify complex philosophical issues (Horn 1998). Formal ways of
‘‘mapping’’ complex information—as opposed to the earth’s surface, countries, cities and
other destinations—began at least 30 years ago, and arguably even earlier.
More recently, the use of information and computer technology has enabled information
mapping to be achieved with far greater ease. A plethora of software tools has been
developed to meet various information mapping needs. What do these tools do? What are
their similarities and differences? What are their advantages and disadvantages? How
precisely do t.
CONCEPT MAPPINGMid Term Assignment (Concept Mapping).docxpatricke8
CONCEPT MAPPING
Mid Term Assignment (Concept Mapping)
Vishvaksen Reddy Kanatala
Dr.Rand Obeidat
Enterprise Risk Management
Our hospital
General checkup
Offers
Medical Attention
Emergencies
of
Regular diseases
Through our
Skilled staffs
Under who conduct
Laboratory experiments
Security
Price consideration
or
to settle
Bill
For an enterprise risk management of health centre, the concepts for the enterprise risk management are the hospital itself, what they offer from medical attention of regular diseases and emergencies as well as a checkup of regular diseases. They the enterprise risk management should focus on how the health centre assures the quality of their service by the use of skilled staffs who conduct laboratory experiment when necessary to ascertain the actual diseases. These services are done at price consideration, or the clients can attack assets which can be used to settle the bill, which should be equivalent to the price consideration.
These concepts relate to each other because enterprise risk management is all about proper control of finances thus for a health centre they, the concept in which they undergo transaction is through the treatment of clients which should be managed effectively and closely monitored to avoid losses. According to the kind of medication given to the client, there should be the amount that the client should pay for the financial stability of the health centre.
The relationship between the concepts in the concept map and the idea to be discussed in the paper is how a hospital goes through until it can reach a point where it can demand payments. The paper is on finances management; thus, the need to show how financial transactions in a hospital are reached t point of declaring the.
The concepts in the concepts maps are connected by the use of verbs as well as conjunctions accordingly to connect one each concept with the other.
Page 1 of 14
BA 308 Leadership & Communication
Hybrid Course Syllabus Spring, 2019
CRN Credits
36093 4
Instructors
Team* Instructor Email** Office Hours Location
A-D Eric Boggs [email protected] Tues. 2pm-4pm 208B Peterson
1-4 Nicole Wilson [email protected] Mon. 10am-12pm 422 Lillis
*Friday Week 1 you will be assigned to a team.
Table of Contents
To quickly find the information you need, press your Ctrl key and click the topic.
Questions & Office Hours ................................................................................................................ 2
What You Should Know About Hybrid Classes ............................................................................. 2
Required Books and Materials........................................................................................................ 3
Canvas Learning Management System ....................................................................................... 3
Course Description ..............
Concept A The first concept that I appreciated in the.docxpatricke8
The document discusses two key concepts - negligence and informed consent. Regarding negligence, it is defined as a failure to act that results in harm to an individual. This could include failing to order dialysis for a patient in need. As a nurse manager, it is important to ensure staff follow policies to avoid negligence and maintain duty of care. The second concept discussed is informed consent, which the Joint Commission defines as a communication process that results in a patient authorizing a specific medical intervention. Informed consent requires fully informing patients on diagnosis, treatment options, risks, benefits and obtaining their signed consent. As a nurse manager, it is critical to ensure all patients undergoing procedures have a valid informed consent form.
Concept Analysis (1,000 words). Deadline 1300, 11 March 2021. .docxpatricke8
Concept Analysis (1,000 words). Deadline: 13:00, 11 March 2021. Concepts lie at the heart of any academic field, and IR is no exception. They help us make sense about the worldand provide a ‘bridge’ between our ideas and the real world. This module will be introducing you to a number of key concepts in IR – as well as some of the debates which swirl around these concepts. This assessment asks youto choose one of these key concepts, and undertake your own research in order to establish the various ways in which the concept is defined and used in the field of IR. You will need to identify and locate appropriate academic sources, engage critically with that material, and construct a piece of writing which conforms to academic conventions.Your analysis needs to be 1,000 words in length, and address the competing meanings of, and debates around, your chosen concept. It needs to be rooted in the field of IR and engage with academic texts which address or use the concept.
The concept is globalisation.
Your concept analysis should address the following aspects:
➢ Who are the main IR theorists who explore this topic
➢ What do they say about this concept?
➢ What are the connections between your chosen concept and other key concepts in IR
In assessing the concept analysis, staff will consider the degree to which:▪ The student’s characterisation of the relevant concept is accurate
▪ The student has engaged with appropriate academic sources
▪ The student has considered a range of definitions, uses and perspectives relating to the concept▪ The analysis is logically and coherently structured
▪ The student has adhered to scholarly conventions in citing sources and producing a bibliography
.
Concentration in the mobile operating systemsmarketMauri.docxpatricke8
Concentration in the mobile operating systems
market
Maurizio Naldi
Universitỳ of Rome Tor Vergata
Department of Computer Science and Civil Engineering
Via del Politecnico 1, 00133 Roma, Italy
[email protected]
Abstract. Concentration phenomena concern the ICT market. Though
the regulatory action has been active mainly in the telecom network
operators industry, even more significant worldwide concentration phe-
nomena affect other industries. The market of mobile operating systems
is analysed through two concentration indices to get a quantitative pic-
ture of the current situation and its evolution over time: the Hirschman
Herfindahl Index (HHI) and the Four-Firm Concentration Ratio (CR4).
A strongly imbalanced oligopoly is shown to exist, where the four major
operating systems take over 99% of the market, but the dominant oper-
ating system Android alone is installed on over 80% of the new devices.
Keywords: Operating Systems; Concentration; Competition; HHI
1 Introduction
Market structure and the presence of dominant operators (manufacturers and/or
service providers) has been a significant field of activity in industrial policy since
long [18]. An operator holding a very large share of the market, or even acting
as a monopolist, may take advantage of its position and enforce unfair poli-
cies towards its customers, which in turn have little or no room to oppose. The
attention for the appearance of dominant positions is at the root of the birth
of a number of national anti-trust agencies, both at the national and superna-
tional level [6], which enforce rules against anticompetitive agreements, abuses
of dominant position as well as concentrations (e.g., mergers and acquisitions,
joint ventures) which may create or strengthen dominant positions detrimental
to competition.
The issue is particularly delicate in ICT industries, where operators may
often benefit of economies of scale, which would lead to a natural monopolistic
structure as the most efficient one [15]. Noam has carried out a broad analysis
of concentration phenomena in several ICT and ICT-related industries [13] [14]:
– Books
– Film
– ISP
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– Magazines
– Multi- channel
– Newspapers
– Online News
– Radio
– Search Engines
– TV
– Wireless
– Wireline
In that survey, the highest HHI value is observed for search engines and is
roughly 0.75, quite above the second highest value, which is 0.55 and pertains
to the wireline telco market.
However, the survey of [13] leaves out a market that has often been at the
center of anti-trust disputes in recent years, which is the operating systems one.
The most notable ones have been the U.S.A. vs Microsoft case for the Windows
desktop operating system [4], and the very recent Statement of Objections raised
by the EU vs Google for the mobile operating system Android [1].
In that Statement of Objections, the European Commission alleges that
Google has b.
Concentric Literary and Cultural Studies 33.1 March 2007 7.docxpatricke8
Concentric: Literary and Cultural Studies 33.1
March 2007: 75-85
Nervous Tracery:
Modern Analogies between Gothic Architecture
and Scholasticism
Joseph C. Murphy
Fu Jen Catholic University
Abstract
During the Gothic revivals of the nineteenth and early twentieth centuries,
Gothic architecture shed the morbid associations attached to it in earlier
periods and was admired for the aesthetic and theological vision that shaped
its medieval development. The Gothic cathedral came to epitomize the
wholeness of the Middle Ages and an impulse toward synthesis in theology as
well as the arts. This essay surveys four Gothic revival texts that define a
relationship between medieval Gothic architecture and Scholastic theology:
John Ruskin’s essay “The Nature of Gothic” in The Stones of Venice (1851-
53); Henry Adams’ Mont Saint Michel and Chartres (1904); Wilhelm
Worringer’s Form in Gothic (Formprobleme der Gotik, 1911); and Erwin
Panofsky’s Gothic Architecture and Scholasticism (1951). In these widely
read works, influential beyond the field of art history, the seemingly arcane
analogy between the Gothic and the Scholastic becomes a proving ground for
the projects of prominent intellectuals within distinct historical and cultural
contexts. For each author, the meaning of the Gothic hangs in a particular
balance between its tracery—that is, its naturalistic ornamental detail—and its
larger structure: the balance between the concrete and the abstract, between
multiplicity and unity, also achieved in Scholastic theology. Because their
analogies between the Gothic and the Scholastic isolate distinct lines of force
within these complex systems, Ruskin, Adams, Worringer, and Panofsky each
identify different values there, revealing as much about the modern mind as
about the medieval. The syntheses that their medieval forbears accomplished
collectively in service of faith, these interpreters seek independently in service
of their own cultural identity, aesthetic values, or intellectual coherence.
Keywords
Gothic architecture, Scholasticism, John Ruskin, Henry Adams,
Wilhelm Worringer, Erwin Panofsky, Thomas Aquinas
Concentric 33.1
March 2007
76
The Gothic style presents an interesting case of how the Middle Ages have
persisted in Western history through the backward glances, sometimes leery,
sometimes wistful, of subsequent periods. First arising in the seventeenth century as
a derogatory term for the anti-classical, “barbarous” style adopted by European
cathedral builders beginning in the twelfth century, the word “Gothic” became
attached in the eighteenth century to a type of sensational narrative set in
infelicitous buildings. During the Gothic revivals of the nineteenth and early
twentieth centuries, Gothic architecture shed its morbid associations and was
admired both for its aesthetic form and for the integral relationship of that form to a
theological vision. Symbolizing, as Arthur Sym.
Con Should the United States government have bailed out the a.docxpatricke8
Con: Should the United States government have bailed out the automobile
industry?
Introduction
A. In 2009, the .“Big Three” (GM, Chrysler, and ford) were facing fmancial struggles.
They were fuced with a decision: either try and work through their problem on their own
by securing loans, or to go to the government for help. Of the Big Three, only Ford
declined government assistance, having already secured a line ofcredit in 2006 by using
all of their assets as collateral. GM and Chrysler filed for a managed Chapter 11
bankruptcy that was funded primarily through the U.S. Treasury using taxpayer money.
This modified version ofChapter 11 bankruptcy that was implemented by the U.S.
government appeared to have allowed these automakers to survive for the time being, but
it came at the expense ofthe taxpayers and it did not address all ofthe problems that
caused the Big Three’s issues in the first place.
I. The Big Three’s poor managerial choices created their financial problems,
and the taxpayers’ money shouldn’t be bailing them out.
A. GM, Chrysler, and ford continued to focus on and mass produce large trucks and
SUVs because of their higher profit margins despite a growing concern over increasing
fuel prices between 2002-2007.
1. Research done by Thomas Klier of the Federal Reserve Bank of Chicago
indicates that during the span of 2002-2007, “about 40 percent of the decrease in
U.S. market share has been caused by the recent increase in the price of gaso line.”
2. More specifically, research done by Meghan Busse and F brian Zettlemeyer of
Northwestern University and Christopher Knittle of UC Berkeley showed that
through the period of 1999-2006, “a$1 increein goIinepricewiII decree
the market share of cars in the least fuel efficient quartile (< 17.7 MPG) by
11.5%.... that a $1 increase in gasoline price will increase the market share of cars
inthemofu effidentquatile(>24.3MR3) by 15.1%”
B. They allowed legacy costs to build by continuing to give out large pension plans when
foreign auto makers were switching to more realistically defined contribution plans
(4OlKs) back in the $Os.
1. The average per-hour base salary ofa U.S. auto worker and a foreign auto
worker were about the same ($28/hour in 2007) but each worker actually cost
$73.21/hour compared to $44.17/hour of Japanese competitors, with the
difference being the additional benefits promised.
C. U.S. autornakers should have switched to defined contribution plans (4OlKs) in order
to stay competitive and keep costs sustainable.
1. GM didn’t officially freeze their pension plans until February of2012.
a. This meant that they would no longer contribute to the pension plans of
workers who were promised them upon employment. Those employees
would now receive 4OlKs (defined contribution plans), a change that
should have been made decades ago to avoid current financial struggles.
II. There was no market failure and the U.S. auto makei should have filed
for traditional Chapter 11 bankrup.
COMS 101
Persuasive Speech Instructions
This course requires you to present a persuasive speech to a live, visually documented audience of 3 or more adults. Use a video recording device to create an audible recording of this presentation for submission. After recording the presentation, upload it to YouTube as an unlisted video and post the video’s link to the instructor via the designated Blackboard assignment submission link. See the Posting Speech Videos to Blackboard via YouTube tutorial (in the Assignment Instructions folder) for step-by-step instruction about this process.
Your speech grade will be determined by the degree to which you satisfy the requirements listed below.
1. Choose an appropriate topic.
This assignment requires you to research a global, national, regional, state or local problem that apparently exists because humans in general or a specific group of humans are neglecting their duty to promote the things God values in this world.
· The problem may be political, economic, educational, environmental, medical, religious, or cultural. It may be a false belief or set of beliefs (about God, nature, or other people) that needs correction, a wrongful attitude or type of attitude (toward God, nature, or other people) that needs adjustment, a neglectful or wrong way of acting (toward God, nature, or other people) that needs to change, or a state of needfulness or brokenness that exists as it does because of human indifference or inactivity.
· The problem must be a social one that deters many individuals—not just a few isolated lives—from experiencing life according to God’s Word as he intended when he created the world the people in it.
Among the social issues that could generate a qualified speech topic are the following:
abortion, infanticide, or euthanasia
discrimination (racism, sexism, ageism)
abuse (child, elder, self, spousal)
ecology (climate change, pollution, littering)
addictions/codependency/eating disorders
education (underachievement or illiteracy)
air, land, or water pollution
famine, drought or diseases
animal abuse or vivisection
labor issues (child labor or sweatshops)
bioethics (cloning, eugenics, stem cell research)
marriage (divorce, cohabitation)
birth or population control
poverty (world hunger or homelessness)
crime (street, juvenile, gang, or white collar)
sex (pre-marital, extramarital, homosexual)
criminal justice (prison crowding, recidivism)
slavery or human trafficking
The following sites may be helpful for discovering or exploring these and other qualified topics:
Center for Bioethics and Human Dignity
The Heritage Foundation
Family Research Council
The Rutherford Institute
The American Enterprise Institute
The Pew Forum on Religion in Public Life
The Discovery Institute
Speech Goals: Because this is a persuasive speech—a speech in which you try to persuade the audience to believe or value something or to act in a specific way—and because you are to use this particular speech to advocate a rede.
COMS 040 AssignmentStudent Congress Bill Choose an argument a.docxpatricke8
COMS 040 Assignment:
Student Congress Bill
Choose an argument and then research it, and write a Congress Bill (a proposed law). (3-5 Whereas clauses) Whereas INSERT FACT IN SUPPORT OF THE BILL/LEGISLATION
Whereas: INSERT FACT IN SUPPORT OF THE BILL/LEGISLATION
Whereas: INSERT FACT IN SUPPORT OF THE BILL/LEGISLATION.
Whereas: INSERT FACT IN SUPPORT OF THE BILL/LEGISLATION.
THEREFORE, BE IT RESOLVED BY THIS STUDENT CONGRESS: insert proposed legislation.
.
computerweekly.com 10-16 September 2019 21Industry experts.docxpatricke8
computerweekly.com 10-16 September 2019 21
Industry experts believe blockchain is a technology that has the potential to affect the business of most IT profession-als in the next five years. Analyst Gartner has forecast that by 2023, blockchain will support the global movement and
tracking of $2tn of goods and services.
It is regarded by many industry watchers as a disrupting force
in the financial world. A PwC global financial technology (fintech)
survey found that 56% of respondents recognise the importance
of blockchain. At the same time, however, 57% admit to being
unsure about or unlikely to respond to this trend.
Start witH tHe HaSH
Blockchain is effectively a shared ledger between a group of
people – for example, a group of companies that work together
to produce a service or product. What makes blockchain differ-
ent is the fact that the history of the changes – past transactions,
for example – are immutable.
Essentially, the historical entries become read-only and
unchangeable. This is due to the fact that each blockchain
entry relies on the hash – a computed value including part of a
previous block as part of its hashing calculation for the current
block. This means that if a previous block is somehow modi-
fied or corrupted, its hash value will change and therefore the
values after that point become broken, making the tampering
evident for all to see.
One example where blockchain technology can be used is
where several companies come together to provide or consume
Blockchain:
hype vs reality
Regarded by many as a
disruptive force in finance
and beyond, blockchain
technology presents a number
of complex challenges that
must be overcome before
it can truly deliver on its
promises. Stuart Burns reports
BUYER’S GUIDE TO BLOCKCHAIN TECHNOLOGY | PART 1 OF 3
Home
IU
R
IIM
O
TO
V
/A
D
O
B
E
http://www.computerweekly.com
https://www.computerweekly.com/resources/Blockchain
https://www.computerweekly.com/ehandbook/Cutting-through-the-blockchain-hype
https://www.computerweekly.com/ehandbook/Cutting-through-the-blockchain-hype
https://www.techtarget.com/contributor/Stuart-Burns
computerweekly.com 10-16 September 2019 22
Home
News
HMRC under fire
over ‘scaremongering’
IR35 letters targeting
GSK contractors
Ransomware has
evolved into a serious
enterprise threat
How Defra has
been preparing its
IT systems for any
Brexit eventuality
Editor’s comment
Buyer’s guide
to blockchain
Chasing down
hackers through
security analytics
How councils are using
technology to support
adult social care
Downtime
services, usually under long-term contracts. It can be complex
and cumbersome to manage contracts involving several individu-
als, when multiple documents are involved and everyone needs
to agree on the same contract versions and details. Over time,
changes will occur that also need to be managed and agreed on.
Managing contracts in blockchain, however, means that rather
than p.
Computers in Human Behavior 39 (2014) 387–392Contents lists .docxpatricke8
Five days at an outdoor education camp without any screen time improved preteen students' ability to interpret nonverbal emotional cues from photos and videos. A group of 51 preteens spent five days at a nature camp without TVs, computers or phones and showed significantly greater gains in recognizing emotions than a control group of 54 students who had normal access to media. Spending time away from screens and immersed in face-to-face social interactions enhanced the camp group's skills at understanding nonverbal emotional cues.
Computers in Human Behavior xxx (2012) xxx–xxxContents lists.docxpatricke8
Computers in Human Behavior xxx (2012) xxx–xxx
Contents lists available at SciVerse ScienceDirect
Computers in Human Behavior
j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / c o m p h u m b e h
Critical thinking in E-learning environments
Raafat George Saadé a,⇑, Danielle Morin a,1, Jennifer D.E. Thomas b,2
a Concordia University, John Molson School of Business, Montreal, Quebec, Canada
b Pace University, Ivan Seidenberg School of CSIS, New York, NY, USA
a r t i c l e i n f o
Article history:
Available online xxxx
Keywords:
E-learning
Critical thinking
Assessment
Information technology
0747-5632/$ - see front matter � 2012 Elsevier Ltd. A
http://dx.doi.org/10.1016/j.chb.2012.03.025
⇑ Corresponding author. Tel.: +1 514 848 2424; fax
E-mail address: [email protected] (R.G. Sa
1 Tel.: +1 514 848 2424; fax: +1 514 848 2824.
2 Tel.: +1 212 346 1569; fax: +1 212 346 1863.
Please cite this article in press as: Saadé, R. G., e
10.1016/j.chb.2012.03.025
a b s t r a c t
One of the primary aims of higher education in today’s information technology enabled classroom is to
make students more active in the learning process. The intended outcome of this increased IT-facilitated
student engagement is to foster important skills such as critical thinking used in both academia and
workplace environments. Critical thinking (CT) skills entails the ability(ies) of mental processes of discern-
ment, analysis and evaluation to achieve a logical understanding. Critical thinking in the classroom as well
as in the workplace is a central theme; however, with the dramatic increase of IT usage the mechanisms by
which critical thinking is fostered and used has changed. This article presents the work and results of
critical thinking in a virtual learning environment. We therefore present a web-based course and we
assess in which parts of the course, and to what extent, critical thinking was perceived to occur. The course
contained two categories of learning modules namely resources and interactive components. Critical
thinking was measured subjectively using the ART scale. Results indicate the significance of ‘‘interactivity’’
in what students perceived to be critical-thinking-oriented versus online material as a resource. Results
and opportunities that virtual environments present to foster critical thinking are discussed.
� 2012 Elsevier Ltd. All rights reserved.
1. Introduction
One of the primary aims of higher education in today’s informa-
tion technology (IT) enabled classroom, is to make students more
active in the learning process (Ibrahim & Samsa, 2009). The in-
tended outcome of this increased IT-facilitated student engage-
ment is to foster important skills such as critical thinking. Given
the importance of information technology for critical thinking in
learning, it is vital that we understand better the associated key
factors related to: background of students, beliefs, perceptions
and attitudes and associated anteceden.
Computers can be used symbolically to intimidate, deceive or defraud.docxpatricke8
Computers can be used symbolically to intimidate, deceive or defraud victims. The basic law that protects our privacy is the Fourth Amendment to the United States Constitution, which mandates that people have a right to be secure in homes and against unreasonable search and seizure. What law(s) have been enacted to protect individuals at the state or federal government? Does these protection laws vary from state to state?
.
Computers are often used to make work easier. However, sometimes c.docxpatricke8
Computers are often used to make work easier. However, sometimes computers can make work more difficult especially with poorly implementation. SOX is an important example of a poorly implemented database that has encountered. A database should have its specific intentions as much as data organization and management always exist as general functions. The SOX database implemented in 2011 was put in place to combat fraud by coming up with efficient accounting audit and management of financial records. I think the developers failed to include technical aspects of fraud control into the system. They instead targeted the visible crimes leaving very many holes for exploiting the SOX system (Anand et al., 2014).
The database seems vague from IT perspective. The database constitutes only two sections of codes relating to IT. These two sections merely meet the standards for testing IT sufficient auditing compliance by organizations. The database seems to be far off the role of fostering sufficient auditing process for these organizations. Since inception, most audit companies struggle to figure out the IT protective aspects of the database. It seems that the developers mainly focused on the guidelines in using financial systems in preventing frauds but rather forgot the IT aspect if reducing the vulnerability of the system. For so many years, the database has failed to meet the technical roles of a database in system management and accounting regulation which are the critical reason why it was created. The SOX guidelines seem to forget about pertinent technical aspects of the system function (Cinarkaya et al., 2017).
The solutions to the mistake that was done are conducting technical analysis and installing appropriate fixing. Ideally, the database should target electronic management and safety of data rather than physical data management. This mistake of poorly implemented gave a false impression of database management in many companies that adopted the type of database in early days. From physical outlook, one could see that things are alright yet some technical rot was brewing within the system. It is clear that the developers of the SOX database missed some point while deriving and implementing the database and this should be fixed to enhance the computer-based operations (Anand et al., 2014).
References
Anand, T. S., Wikle, G. K., Lindsay, M. P., Schubert, R. N., Lettington, D. T., & Ludwig, J. P. (2014). U.S. Patent No. 5,832,496. Washington, DC: U.S. Patent and Trademark Office.
Cinarkaya, B., Tamm, S., Sureshchandra, J., Warshavsky, A., Bulumulla, I. U., Fry, B., ... & Brooks, D. (2017). U.S. Patent No. 9,825,965. Washington, DC: U.S. Patent and Trademark Office.
.
Computers are part of our everyday lives. You are likely reading thi.docxpatricke8
Computers are part of our everyday lives. You are likely reading this assignment on a computer screen right now; you may have a smart phone sitting on your desk, and maybe you just came back from a business trip during which you made airline and hotel reservations online. Over the last several years, you may have noticed that computers are able to store more information and process that information more quickly. New research into the electron spin of atoms hints at a new computer revolution in the near future.
Assignment
For this project, you will be exploring the developments in material science that have allowed computers to become so fast. To do so, please address the following in 3–4 pages, not including title and reference pages:
What are the 3 essential properties of every material?
New materials often lead to new technologies that change society. Describe how silicon-based semiconductors revolutionized computing.
What are microchips? How are they related to integrated circuits?
One of the pressing questions about the increasing ability of computers to quickly process large amounts of information is whether a computer can be built that is considered "alive" or "conscious." What is artificial intelligence? What are 2 essential differences between human brains and the central processing unit of a computer?
Click on the following link to review additional information in a video relevant to this assignment:
Will Computers Out-think Us?
.
Computerized Operating Systems (OS) are almost everywhere. We encoun.docxpatricke8
Computerized Operating Systems (OS) are almost everywhere. We encounter them when we use our laptop or desktop computer. We use them when we use our phones or tablet. Find peer-reviewed articles that discuss the advantages and disadvantages of at least two different Robotic Operating Systems (ROS).
250 words, APA format with references
.
Computerized Operating Systems (OS) are almost everywhere. We en.docxpatricke8
Computerized Operating Systems (OS) are almost everywhere. We encounter them when we use out laptop or desktop computer. We use them when we use our phone or tablet. Find articles that describes the different types of operating systems (Linux, Unix, Android, ROS, z/OS, z/VM, z/VSE, etc).
Do not select MS WINDOWS
. Write a scholarly review of comparing any two or more OS.
It should be at
least 10-15 pages
with at
least 5 APA
citations & matching references.
Formatting
: Introduction; Image / Table; Conclusion; 12 TNR font; double space; clearly divided small paragraphs; bold & underline headings;
.
How to Download & Install Module From the Odoo App Store in Odoo 17Celine George
Custom modules offer the flexibility to extend Odoo's capabilities, address unique requirements, and optimize workflows to align seamlessly with your organization's processes. By leveraging custom modules, businesses can unlock greater efficiency, productivity, and innovation, empowering them to stay competitive in today's dynamic market landscape. In this tutorial, we'll guide you step by step on how to easily download and install modules from the Odoo App Store.
How to Setup Default Value for a Field in Odoo 17Celine George
In Odoo, we can set a default value for a field during the creation of a record for a model. We have many methods in odoo for setting a default value to the field.
Elevate Your Nonprofit's Online Presence_ A Guide to Effective SEO Strategies...TechSoup
Whether you're new to SEO or looking to refine your existing strategies, this webinar will provide you with actionable insights and practical tips to elevate your nonprofit's online presence.
Brand Guideline of Bashundhara A4 Paper - 2024khabri85
It outlines the basic identity elements such as symbol, logotype, colors, and typefaces. It provides examples of applying the identity to materials like letterhead, business cards, reports, folders, and websites.
Level 3 NCEA - NZ: A Nation In the Making 1872 - 1900 SML.pptHenry Hollis
The History of NZ 1870-1900.
Making of a Nation.
From the NZ Wars to Liberals,
Richard Seddon, George Grey,
Social Laboratory, New Zealand,
Confiscations, Kotahitanga, Kingitanga, Parliament, Suffrage, Repudiation, Economic Change, Agriculture, Gold Mining, Timber, Flax, Sheep, Dairying,
How to Manage Reception Report in Odoo 17Celine George
A business may deal with both sales and purchases occasionally. They buy things from vendors and then sell them to their customers. Such dealings can be confusing at times. Because multiple clients may inquire about the same product at the same time, after purchasing those products, customers must be assigned to them. Odoo has a tool called Reception Report that can be used to complete this assignment. By enabling this, a reception report comes automatically after confirming a receipt, from which we can assign products to orders.
A Visual Guide to 1 Samuel | A Tale of Two HeartsSteve Thomason
These slides walk through the story of 1 Samuel. Samuel is the last judge of Israel. The people reject God and want a king. Saul is anointed as the first king, but he is not a good king. David, the shepherd boy is anointed and Saul is envious of him. David shows honor while Saul continues to self destruct.
1. ComputationalModellingofPublicPolicy:
ReflectionsonPractice
Nigel Gilbert1, Petra Ahrweiler2, Pete Barbrook-Johnson1,
Kavin
PreethiNarasimhan1,HelenWilkinson3
1Department of Sociology, University of Surrey Guildford, GU2
7XH United Kingdom
2InstituteofSociology,JohannesGutenbergUniversityMainz,Jako
b-Welder-Weg20,55128Mainz,Germany
3Risk
Solution
s, Dallam Court, Dallam Lane, Warrington, Cheshire, WA2
7LT, United Kingdom
Correspondence should be addressed to [email protected]
Journal of Artificial Societies and Social Simulation 21(1) 14,
2018
Doi: 10.18564/jasss.3669 Url:
http://jasss.soc.surrey.ac.uk/21/1/14.html
Received: 11-01-2018 Accepted: 11-01-2018 Published: 31-01-
2018
2. Abstract: Computationalmodelsare
increasinglybeingusedtoassist indeveloping,
implementingandevalu-
ating public policy. This paper reports on the experience of the
authors in designing and using computational
models of public policy (‘policy models’, for short). The paper
considers the role of computational models in
policy making, and some of the challenges that need to be
overcome if policy models are to make an e�ec-
tive contribution. It suggests that policy models can have an
important place in the policy process because
they could allow policy makers to experiment in a virtual world,
and have many advantages compared with
randomised control trials and policy pilots. The paper then
summarises some general lessons that can be ex-
tractedfromtheauthors’experiencewithpolicymodelling.
Thesegeneral lessonsincludetheobservationthat
o�enthemainbenefitofdesigningandusingamodelisthatitprovides
anunderstandingofthepolicydomain,
rather than the numbers it generates; that care needs to be taken
that models are designed at an appropriate
level of abstraction; that although appropriate data for
calibration and validation may sometimes be in short
supply, modelling is o�en still valuable; that modelling
collaboratively and involving a range of stakeholders
3. from the outset increases the likelihood that the model will be
used and will be fit for purpose; that attention
needstobepaidtoe�ectivecommunicationbetweenmodellersandsta
keholders;andthatmodellingforpub-
lic policy involves ethical issues that need careful
consideration. The paper concludes that policy modelling
will continue to grow in importance as a component of public
policy making processes, but if its potential is to
befullyrealised,
therewillneedtobeameldingoftheculturesofcomputationalmodelli
ngandpolicymaking.
Keywords: Policy Modelling, Policy Evaluation, Policy
Appraisal, Modelling Guidelines, Collaboration, Ethics
Introduction
1.1 Computationalmodelshavebeenusedtoassist indeveloping,
implementingandevaluatingpublicpoliciesfor
at least threedecades,but theirpotential
remainstobefullyexploited(Johnston&Desouza2015;Anzolaetal.
2017;Barbrook-Johnsonetal.2017).
Inthispaper,usingaselectionofexamplesofcomputationalmodelsus
ed
in public policy processes, we (i) consider the roles of models
4. in policy making, (ii) explore policy making as a
typeofexperimentationinrelationtomodelexperiments,and(iii)sug
gestsomekeylessonsforthee�ectiveuse
ofmodels. Wealsohighlightsomeof
thechallengesandopportunities facingsuchmodelsandtheiruse
inthe
future.
Ouraimistosupportthemodellingcommunitythatreadsthisjournalin
itse�orttobuildcomputational
models of public policy that are valuable and useful.
1.2
Webelievethise�ortistimelygiventhatcomputationalmodels,ofthe
typethisjournalregularlyreportson,are
now increasingly used by government, business, and civil
society as well as in academic communities (Hauke
etal.2017).
Therearemanyguidestocomputationalmodellingproducedfordi�er
entcommunities, forexam-
ple in UK government the ‘Aqua Book’ (reviewed for JASSS in
Edmonds (2016)), but these are o�en aimed at
practitioner and government audiences, can be highly
procedural and technical, generally omit discussion of
failure and rarely include deeper reflections on how best to
model for public policy. Our aim here is to fill gaps
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[email protected]
le�bytheseformalguides, toprovidereflectionsaimedatmodellers,
touseaselectionofexamplestoexplore
issues in an accessible way, and acknowledge failures and
learning from them.
1.3 We focus only on computational models that aim to model,
or include some modelling of, social processes.
Although some of the discussion may apply, we are not directly
considering computational models that are
purelyecologicalortechnical intheir
focus,orsimplermodelssuchasspreadsheetswhichmayimplicitlyco
ver
socialprocessesbuteitherdonotrepresentthemexplicitly,ormakeext
remelysimpleandstrongassumptions.
Although ‘computational models of public policy’ is the full
and accurate term, and others o�en use ‘compu-
tational policy models’, for the sake of brevity, we will use the
6. term ‘policy models’ throughout the rest of this
paper.
1.4 Based on our experience, our main recommendations are
that policy modelling needs to be conducted with
a strong appreciation of the context in which models will be
used, and with a concern for their fitness for the
purposes for which they are designed and the conclusions drawn
from them. Moreover, policy modelling is
almost always likely to be of low or no value if done without
strong and iterative engagement with the users
of the model outputs, i.e. decision makers. Modellers must
engage with users in a deep, meaningful, ethically
informed and iterative way.
1.5 In the remainder of this paper, Section 2 introduces the role
of policy models in policy making. Section 3 ex-
ploresthe ideaofpolicymakingasatypeofexperimentation
inrelationtopolicymodelexperiments. Wethen
discusssomeexamplesandexperiencesofpolicymodelling(Section
4)anddrawoutsomekeylessonstohelp
make policy modelling more e�ective (Section 5). Finally,
Section 6 concludes and discusses some key next
steps and other opportunities for computational policy
modellers.
7. TheRoleofModels inPolicyMaking
2.1 Thestandard, butnow somewhatdiscreditedview ofpolicy
making is that itoccurs incycles (forexample, see
the seminal arguments made in Lindblom 1959 and Lindblom
1979; and more recently o�icial recognition in
HM Treasury 2013). A policy problem comes to light, perhaps
through the occurrence of some crisis, a media
campaign, or as a response to a political event. This is the
agenda setting stage and is followed by policy for-
mulation, gathering support for the policy, implementing the
policy, monitoring and evaluating the success of
the policy and finally policy maintenance or termination. The
cycle then starts again, as new needs or circum-
stancesgeneratedemandsfornewpolicies.
Althoughtheideaofapolicycyclehasthemeritofbeingaclearand
straightforwardwayofconceptualisingthedevelopmentofpolicy,
ithasbeencriticisedasbeingunrealisticand
oversimplifying what happens, which is typically highly
complex and contingent on multiple sources of pres-
sureandinformation(Cairney2013;Moran2015),andevenself-
organising (Byrne&Callaghan2014;Teisman&
Klijn 2008).
8. 2.2 The idea of a cycle does, however, still help to identify the
many components that make up the design and
implementationofpolicy. Thereareat
leasttwoareaswheremodelshaveaclearandimportantroletoplay: in
policydesignandappraisal,andpolicyevaluation.
Policyappraisal(asdefinedinHMTreasury2013,sometimes
referred to as ex-ante evaluation, consists of assessing the
relative merits of alternative policy prescriptions in
meetingthepolicyobjectives. Appraisal findingsareakey input
intopolicydesigndecisions. Policyevaluation
either takes a summative approach, examining whether a policy
has actually met its objectives (i.e. ex-post),
or a more formative approach to see how a policy might be
working, for whom and where (HM Treasury 2011).
In the formative role, the key goal is learning to inform future
iterations of the policy, and others with similar
characteristics.
Modellingtosupportpolicydesignandappraisal
2.3 Whenusedex-
ante,apolicymodelmaybeusedtoexploreapolicyoption,helpingtoid
entifyandspecify inde-
tailaconsistentpolicydesign(HMTreasury2013), forexampleby
locatingwherebestapolicymight intervene,
9. or by identifying possible synergies or conflicts between the
mechanisms of multiple policies. Policy models
can also be used to appraise alternative policies, to see which of
several possibilities can be expected to yield
the best or most robust outcome. In this mode, a policy model is
in essence used to ‘experiment’ with alterna-
tive policy options and assumptions about the system in which
it is intervening, by changing the parameters
or the rules in the model and observing what the outcomes are.
This is valuable because it saves the time and
costassociatedwithhavingtorunexperimentsorpilots
intheactualpolicydomain. Thisconceptofthemodel
as an experimental space is discussed in more detail in Section
3 below.
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2.4 Thecommonassumptionisthatonebuildscomputationalmodels
inordertomakepredictions. However,pre-
diction,inthesenseofpredictingthefuturevalueofsomemeasure,isin
facto�enimpossibleinpolicydomains.
10. Socialandeconomicphenomenaareo�encomplex
(inthetechnicalsense,seee.g. Sawyer2005). Thismeans
that how some process evolves depends on random chance, its
previous history (‘path dependence’) and the
e�ect of positive and negative feedback loops. Just as with the
weather, for which exact forecasting is impos-
sible more than a few days ahead, the future course of many
social processes may be literally unknowable in
detail, no matter how detailed the model may be. Secondly, a
model is necessarily an abstraction from real-
ity, and since it is impossible to isolate sections of society,
from outside influences, there may be unexpected
exogenous factors that have not been modelled and that a�ect
the outcome.
2.5 Forthesereasons, theabilitytomake‘pointpredictions’, i.e.
forecastsofspecificvaluesataspecifictimeinthe
future, is rarelypossible. Morepossible
isapredictionthatsomeeventwillorwillnot takeplace,orqualitative
statements about the type or direction of change of values.
Understanding what sort of unexpected outcomes
can emerge and something of the nature of how these arise also
helps design policies that can be responsive
tounexpectedoutcomeswhentheydoarise.
Itcanbeparticularlyhelpful inchangingenvironmentstousethe
11. model to explore what might happen under a range of possible,
but di�erent, potential futures - without any
commitment about which of these may eventually transpire.
Even more valuable is a finding that the model
shows that certain outcomes could not be achieved given the
assumptions of the model. An example of this is
the use of a whole system energy model to develop scenarios
that meet the decarbonisation goals set by the
EU for 2050 (see, for example, RAENG 2015.)
2.6 Ratherdi�erent fromusingmodels
tomakepredictionsorgeneratescenarios is theuseofmodels to
formalise
and clarify understanding of the processes at work in some
domain. If this is done carefully, the model may be
valuable as a training or communication tool, demonstrating the
mechanisms at work in a policy domain and
how they interact.
Modellingtosupportpolicyevaluation
2.7 To evaluate a policy ex-post, one needs to compare what
happened a�er the policy has been implemented
against what would have happened in the absence of the policy
(the ‘counterfactual’). To do this, one needs
12. data about the real situation (with the policy evaluation) and
data about the situation if the policy had not
been implemented (the so-called ‘business as usual’ situation).
To obtain the latter, one can use a randomised
control trial (RCT) or quasi-experiment (HM Treasury 2011),
but this is o�en di�icult, expensive and sometimes
impossibletocarryoutduetothenatureoftheinterventionbarringposs
ibilityofcreatingcontrolgroups(e.g. a
schemewhichisaccessibletoall,orapolicy inwhichlocal
implementationdecisionsare impossibletocontrol
and have a strong e�ect).
2.8 Policy models o�er some alternatives. One is to develop a
computational model and run simulations with and
without implementation of a policy, and then compare formally
the two model outcomes with each other and
with reality (with the policy implemented), using quantitative
analysis. This avoids the problems of having to
establish a real-world counterfactual. Once again, the policy
model is being used in place of an experiment.
2.9 Anotheralternative is
tousemorequalitativeSystemMappingtypeapproaches(e.g.
FuzzyCognitiveMapping;
seeUprichard&Penn2016),
13. tobuildqualitativemodelswithdi�erentstructuresandassumptions(
torepresent
the situation with and without the intervention), and again
interrogate the di�erent outcomes of the model
analyses.
2.10 Finally, another use in ex-post evaluation is to use models
to refine and test the theory of how policies might
have a�ected an outcome of interest, i.e. to support common
theory-based approaches to evaluation such as
Theory of Change (see Clark & Taplin 2012), and Logic
Mapping (see Hills 2010).
2.11 Interrogation of models and model results can be done
quantitatively (i.e. through multiple simulations, sen-
sitivity analysis, and ‘what if’ tests), but may also be done in
qualitative and participatory fashion with stake-
holders, with stakeholders involved in the actual analysis (as
opposed to just being shown the results). The
choice should be driven by the purpose of the modelling
process, and the needs of stakeholders. In both ex-
ante and ex-post evaluation, policy models can be powerful
tools to use as a route for engaging and informing
stakeholders, including the public, about policies and their
implications (Voinov & Bousquet 2010). This may
14. beby includingstakeholders intheprocess, decisions,
andvalidationofmodeldesign; or itmaybe later in the
process, inusingtheresultsofamodel
toopenupdiscussionswithstakeholders,and/orevenusingthemodel
‘live’ to explore connections between assumptions, scenarios,
and outcomes (Johnson 2015a).
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Di�iculties intheuseofmodelling
2.12 While, in principle, policy models have all these roles and
potential benefits, experience shows that it can be
di�icult to achieve them (see Taylor 2003; Kolkman et al. 2016,
and Section 4 for some examples). The policy
process has many characteristics that can make it di�icult to
incorporate modelling successfully, including1:
• The need for acceptability and transparency: policy makers
may fall back on more traditional and more
widelyacceptedformsofevidence,especiallywheretherisksassociat
15. edwiththedecisionarehigh. Mod-
elsmayappeartoactasblackboxesthatonlyexpertscanunderstandoru
se,withoutputshighlyreliant
on assumptions that are di�icult to validate. Analysts and
researchers in government o�en have little
autonomy, and although they may see the value of policy
models, it can be di�icult for them to commu-
nicate this to the decision-makers.
• Changeanduncertainty: theenvironment
inwhichthepolicywillbe implemented,maybehighlyuncer-
tain, this can undermine model development when beliefs or
decisions shi� as a result of the modelling
process (although this is equally an important outcome and
benefit of the modelling process), or other
factors.
• Shorttimescales:
thetimescalesassociatedwithpolicydecisionmakingarealmostalwa
ysrelativelyfast,
and needs can be di�icult to predict, meaning it can be di�icult
for computational modellers to provide
timely support.
• Procurement processes: o�en departments lack the capability
16. and su�iciently flexible processes to pro-
cure complex modelling.
• Thepoliticalandpragmaticrealitiesofdecisionmaking:
individuals’valuesandpoliticalvaluescanhold
hugesway,eveninthefaceofempiricalevidence(letalonemodelling)
thatmaycontradict theirview,or
point towards policy which is politically impossible.
• Stakeholders: There will be many di�erent stakeholders
involved in developing, or a�ected by, policies.
It will not be possible to engage all of these in the policy
modelling process, and indeed policy makers
may be wary of closely involving them in a participatory
modelling process.
2.13 These characteristics may also apply more widely to
evidence and other forms of research and analysis. It is
not our suggestion that these characteristics are inherently
negative; they may be important and reasonable
parts of the policy making process. The important thing to
remember, as a modeller, is that a model can only,
and should only, provide more information to the process, not a
final decision for the policy process to simply
implement.
17. PolicyExperimentsandPolicyModels
3.1 Although the roles and uses of policy models are relatively
well-described and understood, our perception is
that there are still many areas where more use could be made of
modelling and that a lack of familiarity with,
and confidence in, policy modelling, is restricting its use.
Potential users may question whether policy mod-
elling in their domain is su�iciently scientifically established
and mature to be safely applied to guiding real-
world policies. The di�erence between applying policies to the
real world and making experimental interven-
tions in a policy model might be too big to generate any
learning from the latter to inform the former.
Policypilots
3.2 One response is to argue that actual policy implementations
are themselves experimental interventions and
are therefore of the same character as interventions in a policy
model. Boeschen et al. (2017) propose that
we live in “experimental societies" and that implementing
policies is nothing but conducting “real-world ex-
periments". Real-world experiments are “a more or less
18. legitimate, methodically guided or carelessly adopted
social practice to start something new" (Krohn 2007, p. 344;
own translation). Their outcomes immediately
display “success or failure of a design process" (ibid., p. 347).
3.3 A real-world experiment implements one solution for the
policy design problem. It does not check for other
possible solutions or alternative options, but at best monitors
and responds to what is emerging in real time.
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Implementing policies as a real-world experiment is therefore
far from ideal and far removed from the idea of
reversibility in the laboratory. In laboratory experiments the
experimental system is isolated from its environ-
ment in such a way that the e�ects of single parameters can be
observed.
3.4 One approach that tries to bridge the gap between the real-
world and laboratory experiments is to conduct
19. policypilots.
Theuseofpolicypilots(Greenberg&Shroder1997;CabinetO�ice20
03;Martin&Sanderson1999)
as social experiments is fairly widespread. In a policy pilot, a
policy change can be assessed against a coun-
terfactual in a limited context before rolling it out for general
implementation. In this way (a small number of)
di�erent solutions can be tried out and evaluated, and learning
fed back into policy design.
3.5 A dominant method for policy pilots is the Randomised
Control Trial (RCT) (Greenberg & Shroder 1997; Boruch
1997), well-known from medical research, where a carefully
selected treatment group is compared with a con-
trol group that is not administered the treatment under scrutiny.
RCTs can thus present a halfway house be-
tween an idealised laboratory experiment and a real-world
experiment. However, the claim that an RCT is ca-
pableofreproducingalaboratorysituationwhererigoroustestingagai
nstacounterfactual ispossiblehasalso
been contested (Cabinet O�ice 2003, p. 19). It is argued that in
principle there is no possibility of social experi-
mentsduetotherequirementofceterisparibus (i.e.
inthesocialworld, it is impossibletohavetwoexperiments
with everything equal but the one parameter under scrutiny);
20. that the complex system-environment interac-
tions that are necessary to adequately understand social systems
cannot be reproduced in an RCT; and that
random allocation is impossible in many domains, so that a
‘neutral’ counterfactual cannot be established.
Moreover, itmaybeariskypoliticalstrategyorevenunethical
toadministeracertainbenefit insomepilotcon-
textbutnottothecorrespondingcontrolgroup. This
isevenmorethecase if thepolicywouldputtheselected
recipients at a disadvantage (Cabinet O�ice 2003, p. 17).
3.6
Whileapilotcanbegoodforgatheringevidenceaboutasinglecase,
itmightnotserveasagood‘one-size-fits-
all’ role model for other cases in other contexts. Furthermore, it
cannot say much about why or how the policy
workedordidnotwork,ordecomposethe‘whatworks’questions into,
‘whatworks,where, forwhom,atwhat
costs,andunderwhatconditions’?
Therearealsomorepracticalproblemstoconsider,amongthemtime,s
ta�
resources and budget. There is general agreement that a good
pilot is costly, time-consuming, “administra-
tively cumbersome" and in need of well-trained managing sta�
(Cabinet O�ice 2003, p. 5). There is “a sense of
21. pessimismanddisappointmentwiththewaypolicypilotsandevaluati
onsarecurrentlyusedandwereusedin
the past (...): poorly designed studies; weak methodologies;
impatient political masters; time pressures and
unrealistic deadlines" (Seminar on Policy Pilots and Evaluation
2013, p. 11).
3.7
Thus,policypilotscannotmeettheclaimtobeahappymediumbetwee
nlaboratoryexperiments,withtheiriso-
lationstrategiescapableofparametervariation,andKrohn’sreal-
worldexperimentsinvolvingcomplexsystem-
environment interactions in real time. This is where
computational policy modelling comes in.
Policymodels forpolicyexperimentation
3.8 Unlike policy pilots, computational policy models are able
to work with ceteris paribus rules, random control,
andnon-contaminatedcounterfactuals(seebelow).
Usingpolicymodels,wecanexplorealternativesolutions,
simplybytryingoutparametervariations inthemodel,
andexperimentwithcontext-specificmodelsandwith
short,mediumandlongtimehorizons.
Furthermore,policymodelsareethicallyandpoliticallyneutraltobui
22. ld
and run, though the use of their outcomes may not be.
3.9 Unlikereal-
worldandpolicypilots,policymodelsallowtheusertoinvestigatethef
uture. Initiallythemodellers
will seektoreproducethedatabasedescribingthe
initialstateofareal-worldexperimentandthenextrapolate
simulatedstructuresanddynamicsintothefuture.
Atfirstabaselinescenariocanbederived: whatiftherewere
no changes in the future? This is artificial and, for
methodological reasons, boring: nothing much happens but
incremental evolution, no event, no surprise, no intervention;
changes can then be introduced.
3.10 As with real-world experiments, modelling experiments
enable recursive learning by stakeholders. Stakehold-
ers can achieve system competence and practical skills through
interacting with the model to learn ‘by doing’
how to act in complex situations. With the model, it is not only
possible to simulate the real-world experiment
envisagedbutalsototestmultiplescenariosforpotential real-
worldexperimentsviaextensiveparametervari-
ations. The whole solution space can be checked, where future
states are not only accessible but tractable.
23. 3.11 Thisdoesnotimplythatit
ispossibletoobtainexactpredictionsforfuturestatesofcomplexsocia
lsystems(see
the discussion on prediction above). Deciding under uncertainty
has to be informed di�erently:
“Experimenting under conditions of uncertainties of this kind, it
appears, will be one of the most
distinctivecharacteristicsofdecision-makinginfuturesocieties[...],
theyimportandusemethods
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of investigation and research. Among these are conceptual
modelling of complex situations, com-
puter simulation of possible futures, and – perhaps most
promising – the turning of scenarios into
‘real-world experiments’" (Gross & Krohn 2005, p. 77).
3.12 Regarding the continuum between the extremes of giving
24. no consideration (e.g. with laboratory experiments)
and full consideration (e.g. real-world experiments) to complex
system-environment interactions, policy mod-
elling experiments indeed sit somewhere in the (happy) middle.
We would argue that, where the costs or risks
associated with a policy change are high, and the context is
complex, it is not only common sense to carry out
policy modelling, but it would be unethical not to.
ExamplesofPolicyModels
4.1 Wehavediscussedtheroleofpolicymodels
inabstractatsomelength, it isnowimportantto illustratetheuse
of policy models using a number of examples of policy
modelling drawn from our own experience. These have
beenselectedtoo�erawiderangeoftypesofmodelandcontextsofapp
lication. Inthespiritofrecordingfailure
as well as success, we mention not only the ultimate outcomes,
but also some of the problems and challenges
encountered along the way. In the next section, we shall draw
out some general lessons from these examples.
Tell-Me
4.2 TheEuropean-fundedTELLMEproject
25. focusedonhealthcommunicationassociatedwithinfluenzaepidemic
s.
One output was a prototype agent-based model, intended to be
used by health communicators to understand
the potential e�ects of di�erent communication plans under
various influenza epidemic scenarios (Figure 1).
4.3 The basic structure of the model was determined by its
purpose: to compare the potential e�ects of di�er-
entcommunicationplansonprotectivepersonalbehaviourandhence
onthespreadofaninfluenzaepidemic.
This requires two linked models: a behaviour model that
simulates the way in which people respond to com-
munication and make decisions about whether to vaccinate or
adopt other protective behaviour, and an epi-
demic model that simulates the spread of influenza. The key
model entities are: (i) messages, which together
implement the communication plans; (ii) individuals, who
receive communication and make decisions about
whethertoadoptprotectivebehaviour;and(iii)regions,whichholdin
formationaboutthelocalepidemicstate.
The major flow of influence is the e�ect that communication
has on attitude and hence behaviour, which af-
fects epidemic transmission and hence incidence. Incidence
contributes to perceived risk, which influences
26. behaviourandestablishesafeedbackrelationship(seeBadham&Gilb
ert2015forthedetailedspecification). A
fullerdescriptionofthemodelanddiscussiononitusescanbefoundin
Barbrook-Johnsonetal. (2017). Amore
technicalpaperonanovelmodelcalibrationapproachusingtheTellM
easanexampleispresentedinBadham
et al. (2017).
4.4
Drawingonfindingsfromstakeholderworkshopsandtheresultsofthe
modelitself,themodellingteamsuggest
the TELL ME model can be useful: (i) as a teaching tool, (ii) to
test theory, and (iii) to inform data collection
(Barbrook-Johnson et al. 2017).
HOPES
4.5 Practice theories provide an alternative to the theory of
planned behaviour and the theory of reasoned action
to explore sustainability issues such as energy use, climate
change, food production, water scarcity, etc. The
central argument is that the routine activities (aka practices)
that people carry out in the service of everyday
living(e.g. waysofcooking,eating,
travelling,etc.),o�enwithsomelevelofautomaticitydevelopedover
27. time,
shouldbethefocusof inquiryandinterventionif thegoal
istotransformenergy-andemissions-intensiveways
of living.
4.6 The Households and Practices in Energy use Scenarios
(HOPES) agent-based model (Narasimhan et al. 2017)
was developed to formalise key features of practice theories and
to use the model to explore the dynamics of
energyuseinhouseholds. Akeytheoretical
featurethatHOPESsoughttoformalise is theperformanceofprac-
tices, enabled by the coming together of appropriate meanings
(mental activities of understanding, knowing
how and desiring, Reckwitz 2002), materials (objects, body and
mind) and skills (competences). For example,
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Figure 1: A screenshot of the Tell Me model interface. The
interface houses key model parameters related to
individuals’ attitude towards influenza, their consumption of
28. di�erent media types, the epidemiological pa-
rameters of the strain of influenza, and their social networks.
Key outputs shown include changes in people’s’
attitude, actual behaviour, and the progression of the epidemic.
The world view shows the spread of the epi-
demic (blue = epidemic not yet reached, red = high levels of
infection, green = most people recovered).
a laundry practice could signify a desire for clean clothes
(meaning) realised by using a washing machine (ma-
terial) and knowing how to operate the washing machine (skill);
performance of the practice then results in
energy use.
4.7 HOPES has two types of agents: households and practices.
Elements (meanings, materials and skills) are en-
tities in the model. The model concept is that households choose
di�erent elements to perform practices de-
pendingonthesocio-technicalsettingsuniquetoeachhousehold.
Theperformanceofsomepracticesresult in
energy use while some do not, e.g., using a heater to keep warm
results in energy use whereas using a jumper
or blanket does not incur energy use. Furthermore, the repeated
performance of practices across space and
time causes the enabling elements to adapt (e.g. some elements
29. are used more popularly than others), which
subsequently a�ects the future performance of practices and
thereby energy use. A rule-based system, devel-
oped based on empirical data collected from 60 UK households,
was included in HOPES to enable households
to choose elements to perform practices. The rule-based
approach allowed organising the complex contex-
tual information and socio-technical insights gathered from the
empirical study in a structured way to choose
the most appropriate actions when faced with incomplete and/or
conflicting decisions. HOPES also includes
sub-models to calculate the energy use resulting from the
performance of practices, e.g. a thermal model of a
house is built in to consider the outdoor temperature, the type
and size of heater, and the thermostat setpoint
to estimate the energy used for thermal comfort practices in
each household.
4.8 The model is used to test di�erent policy and innovation
scenarios to explore the impacts of the performance
of practices on energy use. For example, the implementation of
a time of use tari� demand response scenario
shows that while some demand shi�ing is possible as a
consequence of pricing signals, there is no significant
reductioninenergyuseduringpeakperiodsasmanyhouseholdscanno
30. tputo�usingenergy(Narasimhanetal.
2017). The overall motivation is that by gaining insight into the
trajectories of unsustainable energy consum-
ing practices (and underlying elements) under di�erent
scenarios, it might be possible to propose alternative
pathways that allow more sustainable practices to take hold.
SWAP
4.9 TheSWAPmodel (Johnson2015b,a) isanagent-basedmodelof
farmers’makingdecisionsaboutadoptingsoil
and water conservation (SWC) practices on their land.
Developed in NetLogo (Wilensky 1999), the main agents
inthemodelarefarmers,whoaremakingdecisionsaboutwhethertopr
acticeSWCornot,andextensionagents
who are government and non-governmental actors who
encourage farmers to adopt. Farmers can also be en-
couraged or discouraged to change their behaviour depending on
what those nearby and in their social net-
worksaredoing.
Theenvironmentisasimplemodelofthesoilquality(Figure2).
Themainoutcomesofinterest
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31. 10.18564/jasss.3669
are the temporal and spatial patterns of SWC adoption. A full
description can be found in Johnson (2015b) and
Johnson (2015a).
Figure 2: Screenshot of the SWAP model key outputs and
worldview in NetLogo. The outputs show the per-
centagesof farmerspracticingSWCandsimilarly thenumberof
fieldswithSWC. Intheworldview,circlesshow
farmer agents in various decision states, triangles show
‘extension’ agents, and the patches’ colour denotes
the presence of conservation (green or brown) and soil quality
(deeper colour means higher quality). Source:
Adapted from Johnson (2015a).
4.10 The SWAP model was developed: (i) as an ‘interested
amateur’ to be used as a discussion tool to improve the
qualityof
interactionbetweenpolicystakeholders;and(ii)asanexplorationoft
hetheoryonfarmerbehaviour
in the SWC literature.
32. 4.11 The model’s use as an ‘interested amateur’ was explored
with stakeholders in Ethiopia. Using a model as an
interestedamateur isaconcept inspiredbyDennett(2013).
Dennettsuggestsexpertso�entalkpasteachother,
make wrong assumptions about others’ beliefs, and/or do not
wish to look stupid by asking basic questions.
These failings can o�en mean experts err on the side of under-
explaining issues, and thus fail to come to con-
sensus or agreeable outcomes in discussion. For Dennett, an
academic philosopher, the solution is to bring
undergraduate students – interested amateurs – into discussions
to ask the simple questions, and generally
force experts to err on the side of over-explanation.
4.12 The SWAP model was used as an interested amateur with a
di�erent set of experts, policy makers and o�icials
in Ethiopia. This was done because policies designed to
increase adoption of SWC have generally been un-
successful due to poor calibration to farmers’ needs. This is
understood in the literature to be a result of poor
interactionbetweenthevariousstakeholdersworkingonSWC.When
used,participantsrecognisedthevalueof
the model and it was successful in aiding discussion. However,
participants described an inability to innovate
in their work, and viewed stakeholders ‘lower-down’ the policy
33. spectrum as being in more need of discussion
tools. A full description of this use of the model can be found in
Johnson (2015a).
INFSO-SKIN
4.13 The European Commission was expecting to spend
arounde77 billion on research and development through
its Horizon 2020 programme between 2014 and 2020. It is the
successor to the previous, rather smaller pro-
gramme,calledFramework7.
WhenHorizon2020wasbeingdesigned,
theCommissionwantedtounderstand
how the rules for Framework 7 could be adapted for Horizon
2020 to optimise it for current policy goals, such
as increasing the involvement of small and medium enterprises
(SMEs).
4.14 An agent-based model, INFSO-SKIN, was built to evaluate
possible funding policies. The model was set up to
reproducethefundingrules,
thefundedorganisationsandprojects,andtheresultingnetworkstruct
uresofthe
Framework 7 programme. This model, extrapolated into the
future without any policy changes, was then used
34. asabenchmarkfor furtherexperiments.
Againstthisbaselinescenario,severalpolicychangesthatwereunder
consideration for the design of the Horizon 2020 programme
were then tested, to understand the e�ect of a
rangeofpolicyoptions:
changestothethematicscopeoftheprogramme;thefunding
instruments; theoverall
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amount of programme funding; and increasing SME
participation (Ahrweiler et al. 2015). The results of these
simulations ultimately informed the design of Horizon 2020.
SilentSpreadandExodis-FMD
4.15 Following the 2001 outbreak of Foot and Mouth Disease
(FMD), the UK Department of the Environment, Food
and Rural A�airs (Defra) imposed a 20-day standstill period
prohibiting any livestock movements o�-farm fol-
lowingthearrivalofananimal. The20-
35. dayrulecausedsignificantdi�iculties for farmers.
TheLessonsLearned
Inquiry, which reported in July 2002, recommended that the 20-
day standstill remain in place pending a de-
tailed cost-benefit analysis (CBA) of the standstill regime.
4.16 Defra commissioned the CBA in September 2002 and a
report was required in early 2003 in order to inform
changes to the movement regime prior to the spring movements
season. This timescale was challenging due
totheshorttimescalesandlimiteddataavailabletoinformthecostrisk
benefitmodellingrequired. Atopdown
model was therefore developed that captured only the essential
elements of the decision, combining them in
an influence diagram representation of the decision to be made.
As wide a range of experts as possible were
involved in model development, helping inform the structure of
the model, its parameterisation, validation
and interpretation of the results. An Agile approach was
adopted with detail added to the model in a series of
development cycles guided by a steering group.
4.17
Theresultant‘SilentSpread’modelshowedthatfactorssuchastimeto
detectionofdisease,aremuchmoreim-