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A non- manipulationist account of inviariance. Federica Russo Philosophy, Kent. Overview. Causal assessment and manipulationism Invariance under intervention and the manipulationist dilemma A non- manipulationist account of invariance Invariance under changes of the environment

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a non manipulationist account of inviariance

A non-manipulationistaccountof inviariance

Federica Russo

Philosophy, Kent


Causal assessment and manipulationism

Invariance under intervention and the manipulationist dilemma

A non-manipulationist account of invariance

Invariance under changes of the environment

Invariance vs variation

Invariance vs regularity

the problem of causal assessment
The problem of causal assessment

E.Coli causes food poisoning

Gravitational interactions between Hearth and Moon cause tides

Ageing populations have an effect on pension and health care systems

Causal assessment is the question of whether A causes B. Granted, it typically needs support from how questions. (RWT)


Information about the results of interventions

is of utmost importance

for explanation or causal assessment

manipulationism and causal assessment
Manipulationism and causal assessment

Empirical generalisations

Change-relating relations between variables

Spurious? Accidental?


Empirical generalisations must show some invariability

in order to be causal


Empirical generalisations must be invariant

under specified interventions on the cause

a manipulationist dilemma
A manipulationist dilemma

Horn 1.


Horn 2.


A method for causal assessment:

Were manipulations on X yield changes on Y,

then we’d be entitled to infer that X causes Y

a) Strictly interpreted

Stuck back into Horn 1

b) Charitably interpreted

Stuck back into Horn (a)

Disingenuous rationale of causal assessment

Truth conditions:

X causes Y if, and only if, manipulations on X

accordingly yield changes on Y

Unilluminatingas to the methods

invariance under changes
Invariance under changes

Observational contexts

Changes in theenvironment

Background knowledge and preliminary analyses of data suggest how to partition the population to test for invariance in different ‘environments’

Stabilityof the model parameters across chosen partitions of the population

example self rated health in baltic countries
Example: self-rated health in Baltic countries

‘Self-rated health’, the response variable (effect), directly depends on ‘Education’, ‘Alcohol consumption’, ‘Locus of control’, ‘Psychological distress’, and ‘Physical health’

what results
What results?

Causal factors

alcohol consumption, physical health, psychological health, psychological distress, education, locus of control, and social support

had a remarkable stable impact on self-rated health

across different environments

the different Baltic countries, across the time-frames analysed, across gender, ethnicity, or age group.

take home message
Take home message

Manipulations are not the building block

of causal assessment.

They are a good tool, when they can be performed

Nota bene

This subsumes rather, than rule out, ‘experimental’ changes, i.e. interventions

Changes in the putative effects due to targeted interventions in the putative cause

invariance of what
Invariance of what?

Invariance of the change-relating generalisations

Variational epistemology / methodology

for invariant change-relating generalisations

variational epistemology
Variational epistemology

Truth conditions – conceptual analysis

Conditions under which a causal claim is true

‘X causes Y’ iff were we to manipulate …

Rationale – epistemology/methodology

Notion underlying causal reasoning/methods

Are there joint variations between X and Y?

Are those variations spurious / invariant / regular /

due to intervention on X …?

variational methodology
Variational methodology

Y = X+

Variational reading

Variations in Y are accompanied by variations in X

May be just observational. Impose further constraints

Manipulationist reading (derived)

Manipulations on X make X vary such that Y varies accordingly

Joint variations between X-Y are due to manipulations

Counterfactual reading (derived)

Were we to vary X, Y would accordingly vary

Joint variations between X-Y are hypothetical

so far
So far …

Causal assessment and the troubles of manipulationism

Non-manipulationist invariance to rescue

Variational epistemology/methodology to underpin invariance

Next time …

  • Invariance vsregularity
  • (or, debunking a false myth)