This document discusses evidence for causal claims in the social sciences. It argues that establishing causation requires multiple types of evidence, including evidence that a cause makes a difference to an effect and evidence about the underlying mechanisms by which the cause produces the effect. Regarding mechanisms, the document reviews debates about how to define mechanisms and proposes that mechanisms in social science are primarily epistemic - they are statistically modeled and have explanatory power even if they do not correspond to physically existing entities. The document also discusses how causal modeling represents mechanisms through recursive decomposition of probabilistic relationships, and how the validity of these models determines whether correlations reflect causal relationships.

1. Evidence in the social sciences
Federica Russo
Philosophy | Humanities | Amsterdam
russofederica.wordpress.com | @federicarusso

2. Flash back

3. WHAT MAKES A CAUSAL MODEL
CAUSAL
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4. A question of validity
A methodological concern thoroughly analysed
since the late ‘60s
Cook & Campbell
Decide whether a model is valid
Successful inferences
Correlations, causal relations, prediction, control, …
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5. Types of validity are about whether:
Statistical conclusion validity
The correlation (covariation) between treatment and
outcome is validly inferred
Internal
Observed covariation between treatment and outcome
reflects a causal relationship, as those variables are
manipulated or measured
Construct and External
The cause-effect relationship holds over variation in
persons, settings, treatment variables, and measurement
variables
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6. Validity is also about evidence
Beyond the ‘Cook & Campbell Tradition’, i.e.:
Representativeness of sample and possibility to
replicate studies
Evidential pluralism
To establish causal claims, we need multiple sources
of evidence
Difference-making and mechanisms
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7. EVIDENCE AND
CAUSAL ASSESSMENT
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8. Causal claims
C causes E
Red meat consumption causes cancer
Poverty causes delinquency
Education lowers child mortality
Exercising reduces cardiovascular disease
…
How do we know that?
What makes a causal claim true /versus/
What evidence supports a causal claim
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9. AN INFERENTIALIST APPROACH
J. Reiss, Causation, Evidence, and Inference, Routledge 2015
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10. Causal claims and evidence
The meaning of causal claims
What can we legitimately infer
Causal claims are inferentially related to evidence claims
Flexibility of causal language and nature of causal relata
Freed-up from the ‘straight jacket’
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11. EVIDENTIAL PLURALISM
Russo & Williamson; Clarke et al; Moneta & Russo
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12. Evidential pluralism
To establish a causal claim we need multiple sources
of evidence:
That C makes a difference to E
Correlations, counterfactuals, …
That C produces E
Mechanisms, processes, …
Russo and Williamson,
Interpreting causality in the health sciences, ISPS 2007
Epistemic causality and evidence-based medicine. HPLS 2011
Clarke et al,
The evidence that evidence-based medicine omits, Preventive Medicine 2013
Mechanisms and the evidence hierarchy, Topoi 2014
Moneta and Russo
Causal models and evidential pluralism in econometrics, Journal of economic
methodology, 2014
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13. EVIDENCE OF DIFFERENCE-MAKING
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14. … that C makes a difference to E
Qualitative differences
Counterfactual reasoning
Hypothesis generation
…
Quantitative differences
Statistical information
Dependencies in the form of statistical correlations
Results of interventions
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15. Correlations, counterfactuals, etc support the
claim that E (causally) depends on C
Needs to be complemented with story about how
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16. EVIDENCE OF PRODUCTION
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17. … how C produces E
A story about how C causes E. Candidates:
Processes
Describing of continuous ‘world lines’ in physics (and possibly social
science)
Mechanisms
Account for organization of parts of a system and of their
interactions
Powers
Postulating (discovering?) modal properties of some parts of
mechanisms
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18. EVIDENCE OF SOCIAL MECHANISMS
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19. WHY MECHANISMS?
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20. Physical (causal) connections
Process theories of causality
Salmon-Dowe approach
A development of Russell-Reichenbach
(world-lines, at-at theory)
Salmon: ‘put the cause into because’
The because is given by the physical, causal process
(Ontic explanation)
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21. Processes in biology?
Machamer, Darden, Craver (2000, p. 7):
Although we acknowledge the possibility that Salmon’s
analysis may be all there is to certain fundamental types
of interactions in physics, his analysis is silent as to the
character of the productivity in the activities investigated
by many other sciences. Mere talk of transmission of a
mark or exchange of a conserved quantity does
not exhaust what these scientists know about
productive activities and about how activities effect
regular changes in mechanisms.
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22. Processes in social science?
Russo (2009, p.26):
The need to look directly at social scientists’ work was motivated by a
possible difference between causal claims that involve reasonably clear
causal mechanisms and causal claims that do not. I went through five case
studies, and it turned out that none of them contains concepts typical of
aleatory causality in order to get an understanding of causal relations—to
borrow Salmon’s terminology again. Instead, statistical causality is
definitively preferred. However, to prefer statistical causality does not ipso
facto rule out mechanisms from the causal talk. […] the question is not
whether or not we aim at identifying causal mechanisms, rather, how do
we come to identify them. Causal mechanisms are not identified
through causal processes and interactions, but, according to
the social scientists’ practice, they are statistically modelled.
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23. THE RECENT DEBATE
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24. Machamer, Darden and Craver:
‘Mechanisms are entities and activities organized such that they are
productive of regular changes from start or set-up to finish or
termination conditions.’ (Machamer, Darden and Craver 2000 p3.)
Glennan:
‘A mechanism for a behavior is a complex system that produces that
behavior by the interaction of a number of parts, where the
interactions between parts can be characterized by direct, invariant,
change-relating generalizations.’ (Glennan 2002b pS344.)
Bechtel and Abrahamsen:
‘A mechanism is a structure performing a function in virtue of its
component parts, component operations, and their organization.
The orchestrated functioning of the mechanism is responsible for
one or more phenomena.’ (Bechtel and Abrahamsen 2005 p423.)
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25. A CONSENSUS
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26. Illari & Williamson:
A mechanism for a phenomenon is composed of entities
and activities organized so that they are responsible for the
phenomenon.
Illari & Williamson give up on:
Regularity
Start up, finishing conditions
Complex system
Mechanistic explanation:
Identification of the phenomenon
Identification of entities and activities involved
Identification of the organisation
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27. Modelling mechanisms
Quantitative causal models model mechanisms
via the ‘recursive decomposition’
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28. What are the causes of self-rated health in
the Baltic countries in the ‘90s?
X Y
Joint probability distribution
P(Ed, Soc, Phy, Loc, Psy, Alc, Self)
Recursive decomposition:
P(Self|Alc, Psy, Loc, Phy)
P(Alc|Ed, Psy, Phy)
P(Psy|Loc, Soc, Phy)
P(Loc|Ed)
P(Phy) P(Soc) P(Ed)
Health survey in the Baltic countries
Why does this represent
a mechanism?
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29. What mechanism?
‘Modelling mechanisms’ is not tantamount to proving a
‘metaphysical account’ of mechanism
No ontological commitment to the (degree of) physical
existence of (social) mechanisms
Mechanisms are primarily epistemic
They have explanatory power
They track something real: making sense of what actually
happens
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30. Difference-making, mechanisms
and validity
To decide whether correlations (=evidence of difference-making)
are causal we have to decide about the
validity of the whole model
That is, whether the mechanism provides
a good enough explanation of the correlations.
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31. The causal interpretation is
model-dependent
Causal conclusions depend on the whole
‘model set up’ from which they are inferred
Statistical information + background knowledge +
causal information
Not a bad thing after all
Causation is not a ‘all or nothing’ affair
Nor a ‘once and for all’ affair
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32. TO SUM UP AND CONCLUDE
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33. Evidence, causal language,
and causal modelling
What is evidence in social science?
Evidence is couched in causal language
And embedded into causal modelling practice
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34. Evidential pluralism
From the health sciences to the social sciences
Not what constitute causation, but what
supports causal claims
That and How are complementary evidential
components
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35. OPEN ISSUES
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36. And social causation?
One word, many things
Causal pluralism, but that’s for next talk!
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