Title: Ontic injustice in modelling : uprooting the value-free ideal
Abstract:
Causal
modelling is sometimes taken to be a value-neutral activity\, given that m
any of the inference procedures are formalized\, and how it looks like the
variables are measuring numerical parameters that couldn't feasibly count a
s value-influenced. I will offer two main lines of reasoning to show that t
his is false\, and that multiple distinctive kinds of injustice can be perp
etrated with ahistorical and supposedly value-free modelling\, especially i
n choice of variables. Recent work on ontic injustice with respect to gende
r categories concerns the way in which the very categories or conceptual di
visions that we use can wrong the people in those categories\, even if the
categories seem\, objectively\, to apply. I will show how this is a broader
problem than just for socially constructed kinds such as gender. Especiall
y in health or biological sciences\, the way we construct causal variables
and select them for systems of variables can be loci of ontic injustice. I
propose that the root of this is attempts to follow the value-free ideal (V
FI). I show that it is meaningless to posit that there is any genuinely val
ue-free way to do these modelling tasks\; instead\, there are value-opaque
ways where the appearance of value-freedom is spurious\, instead reflecting
merely that the values involved match closely to those of the modeller(s).
Furthermore\, even if we grant that someone might be in principle able to
achieve the VFI\, it is morally otiose to even aim at it. To decide to foll
ow the VFI in choosing variables for modelling is to tell those who will be
negatively affected by any failure to achieve the ideal version of the VFI
that consequences to them don't matter. I conclude with some recent cases
to show that we should instead draw on principles from transformative justi
ce in many cases of modelling where the VFI had been supposed to be valid\;
it improves the modelling and outcomes for use of the model more than tryi
ng and failing to achieve to VFI.
Bio:
Holly K.
Andersen is a philosopher of science who works on issues related to causat
ion\, explanation\, and pragmatism. Much of her work concerns causal modell
ing and explanation\, from a metaphysical or foundational perspective and f
rom an applied\, case-study driven perspective. Her PhD is from the History
and Philosophy of Science Department at the University of Pittsburgh\, and
she has been in the Philosophy Department at SFU for 16 years.