Ben Moulton, JD, MPH, provides an overview of the shared decision making policy landscape.
This presentation was part of a Shared Decision Making Month webinar -- Turning Shared Decision Making Policy into a Reality: Can We Really Improve the Quality of Care While Reducing the Costs.
The presentation discusses the conceptual framework for public policy planning in a step-by-step approach. It involves systematic mode, incremental mode, ad-hoc mode, importation mode of policy generation. Before the end, it will cover the aspects of policy implementation and impact assessment processes.
The slides discuss the basic idea about public policy, types of policies, nature of public policy, forms of policies and models/ approaches of the public policies.
Decision Making PowerPoint PPT Content Modern SampleAndrew Schwartz
164 slides include: the 6 C's of decision making, inherent personal and system traps, decision trees, decision making methods and tips, 4 slides on the GOR approach to decision making, common pitfalls in decision making, effective strategies in making decisions, the 8 major decision making traps and how to effectively minimize each, different decision making perspectives, 3 different types of analysis (grid analysis - paired comparison analysis, and cost/benefit analysis), utilizing planning and overarching questions, 4 modes of decision making and 6 factors in decision making plus more.
Using a rational, logical decision making model will help solve most issues. The following model identifies seven steps in the decision making process.
From collective insanity to organisational learning 2019 03 11 brisbane bus...Jorn Bettin
From collective insanity to organisational learning, by caring about the health of feedback loops at all levels of scale and all the places where they are needed. The talk will address the question of how, when, and why feedback loops may fail or get corrupted, and will explore how feedback loops relate to the creation of learning organisations and the design of better products and services.
From artificially intelligent systems towards real thinking tools and human s...Jorn Bettin
From artificially intelligent systems towards real thinking tools and human scale models that improve both human and machine learning
--
In an increasingly software and data-intensive human world, the objective of human-scale computing is to improve filtering, collaboration, thinking, and learning:
1. between humans,
2. between humans and software systems,
3. and between software systems.
This objective is another way of stating the goal of developing a 'language and interaction style' that is better than any formal or informal language reliant on linear syntax.
--------------------------------------
Jorn Bettin is a Partner at S23M and loves building and working with high-performance teams. Jorn works with top-level subject matter experts and transdisciplinary teams to uncover and activate deep domain knowledge.
Jorn has a background in mathematics and his experience covers the following industries: logistics, industrial automation, healthcare, insurance, banking, legal and accounting, telecommunications, electricity, and government.
S23M’s MODA + MODE thinking tools complement Kaizen and agile techniques, enabling people and software systems to interact in the simplest possible way. MODA + MODE techniques create bridges of understanding between disciplines and organisational silos.
Jorn is passionate about open innovation and about addressing challenges that go beyond the established framework of research in industry, government and academia via the quarterly CIIC unconference. He is a co-author of a number of books on model driven product line engineering, is an expert on semantic interoperability, and has worked in methodology leadership roles at IBM in the 1990s.
Jorn is also part of Autistic Collaboration – a mutual support hub for neurodivergent individuals and ventures, and advises clients on the creation of inclusive cultures of innovation and knowledge sharing.
Ben Moulton, JD, MPH, provides an overview of the shared decision making policy landscape.
This presentation was part of a Shared Decision Making Month webinar -- Turning Shared Decision Making Policy into a Reality: Can We Really Improve the Quality of Care While Reducing the Costs.
The presentation discusses the conceptual framework for public policy planning in a step-by-step approach. It involves systematic mode, incremental mode, ad-hoc mode, importation mode of policy generation. Before the end, it will cover the aspects of policy implementation and impact assessment processes.
The slides discuss the basic idea about public policy, types of policies, nature of public policy, forms of policies and models/ approaches of the public policies.
Decision Making PowerPoint PPT Content Modern SampleAndrew Schwartz
164 slides include: the 6 C's of decision making, inherent personal and system traps, decision trees, decision making methods and tips, 4 slides on the GOR approach to decision making, common pitfalls in decision making, effective strategies in making decisions, the 8 major decision making traps and how to effectively minimize each, different decision making perspectives, 3 different types of analysis (grid analysis - paired comparison analysis, and cost/benefit analysis), utilizing planning and overarching questions, 4 modes of decision making and 6 factors in decision making plus more.
Using a rational, logical decision making model will help solve most issues. The following model identifies seven steps in the decision making process.
From collective insanity to organisational learning 2019 03 11 brisbane bus...Jorn Bettin
From collective insanity to organisational learning, by caring about the health of feedback loops at all levels of scale and all the places where they are needed. The talk will address the question of how, when, and why feedback loops may fail or get corrupted, and will explore how feedback loops relate to the creation of learning organisations and the design of better products and services.
From artificially intelligent systems towards real thinking tools and human s...Jorn Bettin
From artificially intelligent systems towards real thinking tools and human scale models that improve both human and machine learning
--
In an increasingly software and data-intensive human world, the objective of human-scale computing is to improve filtering, collaboration, thinking, and learning:
1. between humans,
2. between humans and software systems,
3. and between software systems.
This objective is another way of stating the goal of developing a 'language and interaction style' that is better than any formal or informal language reliant on linear syntax.
--------------------------------------
Jorn Bettin is a Partner at S23M and loves building and working with high-performance teams. Jorn works with top-level subject matter experts and transdisciplinary teams to uncover and activate deep domain knowledge.
Jorn has a background in mathematics and his experience covers the following industries: logistics, industrial automation, healthcare, insurance, banking, legal and accounting, telecommunications, electricity, and government.
S23M’s MODA + MODE thinking tools complement Kaizen and agile techniques, enabling people and software systems to interact in the simplest possible way. MODA + MODE techniques create bridges of understanding between disciplines and organisational silos.
Jorn is passionate about open innovation and about addressing challenges that go beyond the established framework of research in industry, government and academia via the quarterly CIIC unconference. He is a co-author of a number of books on model driven product line engineering, is an expert on semantic interoperability, and has worked in methodology leadership roles at IBM in the 1990s.
Jorn is also part of Autistic Collaboration – a mutual support hub for neurodivergent individuals and ventures, and advises clients on the creation of inclusive cultures of innovation and knowledge sharing.
From artificially intelligent systems towards real thinking tools and human s...Jorn Bettin
In an increasingly software and data-intensive human world, the objective of human-scale computing is to improve filtering, collaboration, thinking, and learning:
1. between humans,
2. between humans and software systems,
3. and between software systems.
This objective is another way of stating the goal of developing a 'language and interaction style' that is better than any formal or informal language reliant on linear syntax.
From project to product mindset and onwards to product platform architecturesJorn Bettin
Is it possible to stay innovative and economically manage many hundreds or even thousands of products or product variants?
Organisations interested in benefiting from a product line and product platform approach must adopt values and organisational principles that encourage the development of deep domain expertise. This includes a deep understanding of the forces that continuously change the environment of the product line. These forces can then be harnessed as part of the architectural foundation for the product line.
The pervasive digitisation of services and the desire to create and operate platforms that can support large digital service ecosystems that include many organisations, have put the spotlight on design principles for product lines, product platforms, and related organisational structures.
These slides relate to a talk at ProductTank Auckland (https://www.meetup.com/ProductTank-Auckland/events/252496542/). The video recording is available at https://twitter.com/pmauckland/status/1021272934416109568.
Advanced modelling made simple with the Gmodel metalanguageJorn Bettin
Introductory slides on semantic modelling. Not necessarily self explanatory without sound track. See http://mdi2010.lcc.uma.es/proceedings/MDI2010-Proceedings.pdf and http://semanticmodelling.blogspot.com/ for further details.
Attending a job Interview for B1 and B2 Englsih learnersErika906060
It is a sample of an interview for a business english class for pre-intermediate and intermediate english students with emphasis on the speking ability.
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A personal brand exploration presentation summarizes an individual's unique qualities and goals, covering strengths, values, passions, and target audience. It helps individuals understand what makes them stand out, their desired image, and how they aim to achieve it.
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1. From Muddling
to Modelling
in software, economics, engineering, science
2. instance ? class ?
encrypting ? coding ?
modelling ? muddling ?
Golf
ABC 123
model ? object ?
3. Dictionary definition: to code
express (a statement or communication) in an indirect
way
Coding can be viewed as having to deal with
someone else’s representation (program notation
or otherwise)
Dictionary definition: to model
devise a representation, especially a mathematical one
of (a phenomenon or system)
Modelling can be viewed as dealing with a
representation that is fit for purpose
8. Observation: Models are a way of referring
to useful sets or subsets in a domain
Observation:
The elements of a set may
change over time
Definition:
Golf A query is a function that
Golf returns the content of a set at
cars a given point in time
9. Observation: Only one car with
reg # ABC 123 can exist at any given time
cars with
reg # ABC 123
ABC 123
Definition:
An instance is a set
that contains one and
ABC 1
only one element at 23
ABC 12
3
any given point in time
11. Definition:
Instantiation is a model
function that returns
an instance
model
instance
model
instantiation
Golf
of ABC 123
12. model
instantiation
of
Observation: If the
intermediate subsets cars
and Golf are not relevant to
instance
our model, we can use an
instantiation function from a
higher level of abstraction ABC 123
14. View points
subset of
subset of
Golf
sales ABC 123
person
ABC 123 is an instance of Golf
15. View points
subset of
Golf is an instance of cars
engineer
Golf
sales ABC 123
person
ABC 123 is an instance of Golf
16. View points
cars is an instance of objects software platform
Golf is an instance of cars
engineer
Golf
sales ABC 123
person
ABC 123 is an instance of Golf
17. engineer
Golf Golf
is an
ABC instance
123 of ca
is an rs
insta
nce o
f Golf
Communication ?
ABC 123
Golf
sales person
18. Abstractions must be validated via instantiation
Golf
abstract
instantiate
ABC 1
23
engineer sales person
20. No support for multi-level instantiation in any
industry standard modelling/programming language !
cars is an instance of objects
engineer
Golf Golf is an instance of cars
sales person
ABC 123 is an instance of Golf
ABC 123
21. Pragmatic kludge: design time
The Power Type pattern
Class : Mammal
Class : AnimalSpecies
dateOfBirth
maxAge [1] [*]
configuration
A.S. : Dog
{20 years}
time? Class : Dog
isPoliceDog [2]
Class : Cat
[2]
A.S. : Cat
{30 years} [*] [*]
Dog : Jack Cat : Coco
Observation: Today’s
{1/5/03, yes} {4/3/07}
Dog : Susie Cat : Peter
software contains a {1/2/00, no} {10/9/98}
significant amount of
avoidable, spurious
complexity run time
24. Potentially useful semantics
<=> ( ABC 123 : ) U ( ... ) U ...
Joe
<=> ( ABC 123 : ) U ( ... ) U ...
Joe
<=> ( :(
U
ABC 123
)) U ...
Joe
25. We constantly rely on speculative interpretation
<=> airplane or aircraft ?
<=> commercial aircraft ?
<=> ship or boat ?
<=> ferry or cruise ship ?
<=> car ferry ?
<=> paddler or boat ?
Observation: It works 80% of the time
26. Perhaps 80% is not quite good enough
for software specification !
Golf
abstract
instantiate
ABC 1
23
Observation: We need less
speculation and much more
validation via instantiation !
28. Is code any better?
use case step (end user needs)
software design (voodoo)
whizBangTech.createStandardOrder(whizBangTech.createPartner(“Joe”), vwGolf, blue, 1);
code (implementation)
29. Is code any better?
The code is the design.
Yeah, right!
use case step (end user needs)
software design (voodoo)
whizBangTech.createStandardOrder(whizBangTech.createPartner(“Joe”), vwGolf, blue, 1);
code (implementation)
30. model (specification)
use case step (end user needs)
Automation (generation, execution)
whizBangTech.createStandardOrder(whizBangTech.createPartner(“Joe”), vwGolf, blue, 1);
code (implementation)
31. model (specification)
use case step (end user needs)
whizBangTech.createStandardOrder(whizBangTech.createPartner(“Joe”), vwGolf, blue, 1));
code (implementation)
32. Observation: Instantiation links do not adhere to the
simplistic rules of the traditional class/object paradigm ...
under-specified
instance of the VWGolf
product line
nearly fully-specified instance
only here the instance is
fully-specified
Observation:
Partial, incremental instantiation is common in product lines
34. object oriented model A object oriented model B
(modelling instantiation via association) (modelling instantiation via specialisation)
Class : Mammal
Class : AnimalSpecies Class : Animal
[2] dateOfBirth
maxAge dateOfBirth
[1] [*] problem
no species
[*]
data
A.S. : Dog
{20 years} Class : Dog Class : Cat
isPoliceDog [2] [2]
A.S. : Cat
{30 years} [*] [*]
Dog : Jack Cat : Coco
Animal : Jack Animal : Coco {1/5/03, yes} {4/3/07}
{1/5/03} {4/3/07}
Dog : Susie Cat : Peter
Animal : Susie Animal : Peter {1/2/00, no} {10/9/98}
{1/2/00} {10/9/98}
problem
no species-specific
instance data problem
precision of links
35. object oriented model C
(Power Type pattern)
Class : Mammal
Class : AnimalSpecies
dateOfBirth
maxAge [1] [*]
problem
Fragmentation of
concepts
A.S. : Dog
{20 years} Class : Dog Class : Cat
isPoliceDog [2] [2]
A.S. : Cat
{30 years} [*] [*]
problem
Spurious complexity
Dog : Jack Cat : Coco
{1/5/03, yes} {4/3/07}
Dog : Susie Cat : Peter
{1/2/00, no} {10/9/98}
36. object oriented model C design time
(Power Type pattern)
Class : Mammal
Class : AnimalSpecies
dateOfBirth
maxAge [1] [*]
configuration
A.S. : Dog
{20 years}
time? Class : Dog
isPoliceDog [2]
Class : Cat
[2]
A.S. : Cat
{30 years} [*] [*]
Dog : Jack Cat : Coco
{1/5/03, yes} {4/3/07}
Dog : Susie Cat : Peter
{1/2/00, no} {10/9/98}
run time
38. multi-level modelling Vertex : AnimalSpecies system
precise instantiation semantics
role based binding times
maxAge
isAbstract : no design time
modularity
simplicity
instantiation ...
AnimalSpecies : Mammal species
establishes connections between
two levels of abstraction that
define different binding times
maxAge : 150
isAbstract : yes
dateOfBirth
configuration
time
generalisation/specialisation ...
expresses the commonalities and a consistent instantiation
variabilities between the concepts mechanism at all levels
relevant to a specific binding time and unlimited levels of
AnimalSpecies : Dog AnimalSpecies : Cat
instantiation
maxAge : 20 [2] maxAge : 30 [2]
isAbstract : no isAbstract : no
isPoliceDog [*] [*]
treatment time
Dog : Jack Dog : Susie Cat : Coco Cat : Peter
dateOfBirth : 1/5/03 dateOfBirth : 1/2/00 dateOfBirth : 4/3/07 dateOfBirth : 10/9/98
isPoliceDog : yes isPoliceDog : no
39. More Information
The role of artefacts tiny.cc/artefacts
Model Oriented Domain Analysis tiny.cc/domainanalysis
Multi-Level Modelling tiny.cc/gmodel
tiny.cc/sematpos_jbe,
SEMAT
tiny.cc/sematslides_jbe
Denotational Semantics tiny.cc/densem
Thank you!
Jorn Bettin
jbe @ sofismo.ch