2. TOPICS
1. Changes in thinking
2. Demise of narrow scientism
3. A systemic approach to problem solving
4. Introducing a range of systems approaches
5. Emerging premises for SI development
3. CHANGES IN THINKING
FROM SCIENCE TO SYSTEMS
Paradigm (Webster, 1995):
Pattern, clear or typical example or archetype, philosophical and
theoretical framework
4. DEMISE OF NARROW SCIENTISM
Scientism (Webster, 1995):
(1) Methods and attitudes typical attributed to the natural scientist; (2)
exaggerated trust in the efficiency of natural science applied to all areas of
investigation as in philosophical, social sciences, and humanities.
Scientific method (Webster, 1995):
Principles and procedures for the systematic pursuit of knowledge involving
the recognition nad formulation of a problem, the collection of data through
observation and experiment, and the formulation and testing of hypotheses.
5. DEMISE OF NARROW SCIENTISM
Reductionism (Webster, 1995):
(1) attempt to explain all biological processes by the same explanations that
chemists and physicists use to interpret inanimate matter; (2) a procedure
or theory that reduces complex data or phenomena to simple terms
Problems:
Partial analysis
Answers leading to greater problems
6. DEMISE OF NARROW SCIENTISM
Holism (Webster, 1995 & MacDonald, 1979):
(1) A theory that the universe and living nature is correctly seen in terms of
interacting wholes, that are more than the mere sum of elementary particles;
(2) fundamental principle of the universe is the creation of wholes —
complete and self-contained from the cell to the most complex forms of life
Benefit:
Deal with complex wholes without losing their complexity
Ask wider questions
7. SYSTEM APPROACHES TO
PROBLEM SOLVING
System (Senge et al, 1994):
A perceived whole whose elements ‘hang together’ because they
continually affect each other over time and operate toward a common
purpose.
Features of systems:
Identification of boundary Goal seeking
Interaction with the environment Being purposeful
Being closed / open Exerting control
8. SYSTEM APPROACHES TO
PROBLEM SOLVING
Basis for a system approach:
1. The application of a system depend on the individual or shared perception
of onlookers.
2. Once defined, a system has a boundary, established by the onlookers /
stakeholders.
3. A system takes place in a larger environment
4. A system is changing / self-changing.
9. SYSTEM APPROACHES TO
PROBLEM SOLVING
Comparisons of systems and reductionist approaches
System Reductionist
The problem is shared by
legitimate shareholders
A wholeness is reviewed
The environment affects the system
The boundary is flexible,
dependent on the stakeholders’
perception
The problem is in the mind of the
scientists.
A part of a complex whole is
analyzed
The environment is expected to be
controlled
The boundary is defined by the
expert.
10. A RANGE OF SYSTEM APPROACHES
1. Soft-system method
2. Learning organization
3. Participatory rural appraisal
4. Logical framework
11. A RANGE OF SYSTEM APPROACHES
Soft-System Method
12. A RANGE OF SYSTEM APPROACHES
Learning Organization
The Five Disciplines
Disciplines Expected Outcome
Systems Thinking
Personal mastery
Mental Models
Shared vision
Team learning
Description and insight
Empowerment
Clear self-analysis
Organization-wide clarity of purpose
Groups consensus
13. A RANGE OF SYSTEM APPROACHES
Participatory Rural Appraisal
14. A RANGE OF SYSTEM APPROACHES
Logical Framework
Activities Verifiable
Indicators
Means of
Verification
Assumption
Goal
Purpose
Outputs
Measures to
verify
Sources of data
to verify status
Important events,
conditions,
decisions outside
the control
16. EMERGING PREMISES FOR SI DEVELOPMENT
Premises:
1. Sustainability can provide a qualitative measure of the integral nature and
wholeness of any system.
2. Subjectivity of stakeholders in any system is unavoidable
3. Subjectively derived measures of sustainability are useful if it is accepted
and declared at the beginning.
4. Measures of sustainability can be valuable for planning, forecasting and
awareness-building
5. Rapid and participatory tools for developing our thinking and modelling are
valuable to stakeholders within development policy
Editor's Notes
Ch1: concept of sustainability, problem & need for measurement & sustainability indicators (SI), Ch 2.: indicators e.g: maximum sustainable yield (MSY), a general method for ecosystem description & assessment (AMOEBA). Ch3: concept of sustainable cities, communities & development instutions and projects.
Classic: often political & theoretical. SI (sustainability indicators) : reduction to detail. Line means continuum / spectrum.
Alternative: systemic approach complement SI & recognize contributions from local people. SI hegemony of technocrat.
Advance human thoughts and discovery.
Negative: difficult & lose focus
Features: 1. system is distinct from its environment. 2. environment affects the system 3. interrelation beyond its boundary 4. capable of changing behavior 5. select goals 6. retains identity under changing circumstances
4. Seek its own optimum.
So, a system is interesting: 1. a construct of stakeholders’ mind. 2. whole and changing. 3. change for its own sustainability.
Gambar: system view & reductionist
Feature: much time in step 1-2-3 (problem has many definitions, based on the contexts). Compare concept & problem in step 4-5. discuss the analysis with stakeholders in step 6. process is cyclical
1. focus on links / loops (reinforcing / balancing). 2. personal vision, see reality clearly, commitment to result. 3. based on experience, reflection and enquiry 4. collective purpose, speak from the heart, creative tension. 5. learning through conversation & discuss.
Behavior: can do, own judgment, respect, embrace error, don’t rush, have fun. Methods: interview, diagram, compare, estimate, act, monitor, evaluate. Share: share knowledge and analysis, partnership
Goal: vision (sustainable city). Purpose: effect of the project (clean air). Output: deliverable (zero days of air poor quality)