Cejka, Timotej (2022) Reflexivity of Predictions as a Statistical Bias. In: UNSPECIFIED.

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Abstract

It has been argued that reflexive predictions pose a methodological problem to the social sciences by jeopardizing objective theory testing. This problem apparently arises from a reflexive prediction’s ability to modify the evidential import conferred by an observation upon a tested theory. As a classic example, reflexive predictions can lead to a spurious confirmation of a theory (Merton, 1949). In a recent article, Kopec has argued that spurious confirmations constitute just one of multiple undesirable consequences of reflexive predictions, which he argues include both overstating and understating an observation’s evidential support as well as mistaking counter-evidence for evidence (Kopec, 2011). I agree that reflexive predictions may alter the evidential import of an observation; however, I will argue that this is not a genuinely methodological problem for social science but instead a technical one. Specifically, I will show that the reflexivity of a prediction is merely a type of statistical bias and, as such, can be dealt with using standard econometric methods. After developing a new definition of reflexive predictions, I will show that econometric methods can in principle eliminate reflexivity from the predictions used to test theories in social science.

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Item Type:	Conference or Workshop Item (UNSPECIFIED)
Creators:	Creators Email ORCID Cejka, Timotej 0000-0002-9550-2585
Keywords:	reflexive prediction, causal explanation
Subjects:	Specific Sciences > Economics General Issues > Evidence Specific Sciences > Probability/Statistics
Depositing User:	Timotej Cejka
Date Deposited:	27 Oct 2022 15:49
Last Modified:	27 Oct 2022 15:49
Item ID:	21326
Subjects:	Specific Sciences > Economics General Issues > Evidence Specific Sciences > Probability/Statistics
Date:	May 2022
URI:	https://philsci-archive.pitt.edu/id/eprint/21326

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