causalanalysis systemics dubrovnik
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Mechanisms and systems: Mechanisms and systems: causal issues in the social sciencescausal issues in the social sciences
Federica RussoPhilosophy, Louvain & Kent
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OverviewCausal modelling
MethodologyPresuppositions
System analysisPresuppositionsMethodology
Causal modelling vs. Systemics
A case studyHealth systems and mortality
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Causal modellingGoals
Detecting causes of effectsMeasuring effects of causesUncovering causal structuresModelling causal mechanisms…
MethodsQualitative/QuantitativeAggregate/Individual/Multilevel…
MethodologyHypothetico-deductivism
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Causal models are made ofAssumptions
StatisticalExtra-statisticalCausal
Key notionsBackground knowledgeExogeneityInvariance/StabilityClosure of the system
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Causal assumptions
Covariate sufficiencyAll the variables included in the modelare needed to explain the phenomenon
No-confoundingNo variable included in the modelscreens-off other variables
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Working hypothesis: the system is closed
Strict closureThe system described is not subject to any external influence
X Y
R V
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Working hypothesis: the system is closed
Weak closureVariables in the model undergo influencesfrom non-observed variables non correlatedbetween themselves
X Y
R VI1 I2
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Working hypothesis: the system is closed
Failure of closureVariables in the model undergo influencesfrom non-observed variables that arecorrelated between themselves
X Y
R V
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Causal models model mechanisms
Mechanisms are a scheme ofhow variables relate to each other
Variables play specific (causal) roles
Some types of relations are excluded,e.g. loops
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Hypothetico-deductivismHypothesise stage and prior information
Causal hypotheses are (dis)confirmeddepending on results of tests andon congruence with background knowledge
A dynamic processVa et vient between established theoriesand establishing theories
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System analysis: scope and goals
System theoristsvon Bertalanffy (1969), Bunge (1979)
A general theory of systemsin the various sciences
Formulation and derivation ofprinciples valid for all systems
Systems are ubiquitous,a general framework is needed
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von Bertalanffy:Major aims of a general system theory (1969):
1. there is a general tendency towards the integrationin the various sciences, natural and social;
2. such integration seems to be centredin a general system theory;
3. such theory may be an important means of aimingat exact theory in the non-physical fields of science;
4. developing unifying principles running ‘vertically’through the universe of the individual sciences;
5. this can lead to a much-needed integrationin scientific education.
General system theory aims toencompass various disciplines.
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What is a system?A system is a set of elements standingin reciprocal interrelations
Elements, p, stand in relation, R, so that the behaviour of an element p in R is different from its behaviour in another relation, R’. If the behaviours in R and R’ are not different, there is no interaction, and the elements behave independently with respect to the relations R and R’.(von Bertalanffy 1969, p.37)
Systems are mathematically definedby certain families of differential equationsSystems are not aggregates
(= collections of items not held togetherby bonds and lacking integrity)
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Systems and the wholeScience of the whole
Holism:stresses integrity of systems at the expenses oftheir components and of mutual actions among themAtomism:the whole is contained in its parts, so the studyof parts suffices to understand the whole
Neither can properly analyse systems
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Systemics methodology (Bunge)
Firstidentification of the components of the system
Secondidentification of the environment
Thirdidentification of the structure
N.B.: no prior hypotheses about the structure
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Systemics, a different worldview
von Bertalanffy:systemics open a new paradigm
System philosophyAgainst the analytic, mechanistic,one-way causal paradigm of classical science
No sharp difference betweenthe object of investigation and the knowing
agent
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A different worldviewvon Bertalanffy (1969)
Perception is not a reflection of ‘real things’ (whatever their metaphysical status), and knowledge is not a simple approximation to ‘truth’ or ‘reality’. It is an interaction between knower and known, this dependent on a multiplicity of factors of a biological, psychological, cultural, linguistic, etc., nature.
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A different worldviewVon Bertalanffy (1969)
The third part of systems philosophy will be concerned with the relations of man and world or what is termed ‘values’ in philosophical parlance. If reality is a hierarchy of organized wholes, the image of man will be different from what it is in a world of physical particles governed by chance events as ultimate and only ‘true’ reality. Rather, the world of symbols, values, social entities and cultures is something very ‘real’; and its embeddedness in a cosmic order of hierarchies is apt to bridge the opposition of C.P. Snow’s ‘Two Cultures’ of science and the humanities, technologies and history, natural and social sciences, or in whatever way the antithesis is formulated.
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A different worldviewBunge (1979):
There are no stray things
Every thing interacts with everything elseso that all things cohere in forming systems
Every concrete thing is either a systemor a component of it
Every system is engaged in some process or other
Every change in a system is lawful
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Causal modelling vsvs. system analysis
Closure of the systemand mechanisms
The agent is external
Causal mechanisms are
established usingprior information
Every thing interactswith everything else
The agent is internal
Structures are identified
without prior information
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Causal analysis withinwithin system analysis?
Lauriaux (1994)theoretical weaknesses of causal analysis:
choice of variables, conceptualisation,closure of the system
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A case study:health system and mortality
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X1Economic
development
X2Social
development
X3Sanitary
infrastructures
X4Use of sanitary infrastructures
X5Age structure
YMortality
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Lauriaux’s critiquePrincipal variables are theoretical constructsaccording to well established economicand sociological theories
Assumption: economic developmentgenerates social development
Problem: counterexamples exist, the arrowmight be reversed with serious problems for policy
To intervene on an effect which is not an effectwon’t deliver the planned results
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Causal analysis withinwithin system analysis?
The problem still remains:How to make sense of covariationsbetween variables if we abandonthe causal framework?
Solution: system analysis
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ComplementarityComplementarityof the two approaches?
Systems are homeostatic:they keep themselves in a stable state by meansof regulatory interdependent mechanisms
Changes in the system re-establish theequilibrium in consequence of too stronginternal/external influences
In the process of balancing,components jointly evolve
Those joint evolutions are covariationswe call causal
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Lauriaux’s systemic story
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My systemic worriesSystems become very easily
intractable,of difficult use for policy
I haven’t seen precise,concrete methods to analyse data
Assumptions clash too much to makethe approaches complementary
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To sum upI sketched the features
Of causal modelling: closure of the system, use of prior information, mechanism
Of system analysis: different worldview, reciprocal interrelations of elements
I discussed the possibility of acomplementarity of the two approaches
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A charitable interpretation?
A weak notion of ‘system’Mechanisms are within (social) systemsRelax postulate that every thing interacts
with everything else
A weak and diversified notion of ‘interaction’The agent interacts with the system: she
interprets but doesn’t modify itThings can have correlational, causal, …,
interactions
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To concludeAre those approaches compatible?
I think not, because of significantlydifferent assumptions
Is systemics a viable alternative?I think not, because clear methodsare still lacking
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Unless …A charitable interpretation ofsystems and interaction is provided
Peculiar import of systemicsis perhaps distort
Yet causal modelling gains … ?
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References Bunge M. (1979). A world of systems. Reidel Publishing Company.Franck R. (1994) (ed). Faut-il chercher aux causes une raison? Vrin.Franck R. (2002) (ed). The Explanatory Power of Models. Springer.Lauriaux M. (1994), “Des causes aux systèmes: la causalité en question”,
in Franck (1994).Lopez-Rios O., Mompart A. and Wunsch G. (1992). Système de soins et
mortalité régionale: une analyse causale, European Journal of Population, 8(4), 363-379.
Pumain D. (2006) (ed). Hierarchy in natural and social sciences. Springer.Russo F. (forthcoming), Measuring variations. Causality and causal
modelling in the social sciences. Springer.von Bertalanffy (1969), General system theory. Braziller.