Revisiting and Rethinking the Identifiable Victim Effect: Replication and Extension of Small, Loewenstein, and Slovic (2007)

Author:

Maier Maximilian12ORCID,Wong Yik Chun34,Feldman Gilad56ORCID

Affiliation:

1. Department of Experimental Psychology 1 ,

2. University College London, London UK 1 ,

3. Department of Psychology 2 ,

4. University of Hong Kong, University of Hong Kong, Hong Kong SAR 2 ,

5. Department of Psychology 3 ,

6. University of Hong Kong, Hong Kong SAR 3 ,

Abstract

The identifiable victim effect describes the stronger tendency to help a specific victim than to help a group of unidentified statistical victims. Our reanalysis of a meta-analysis on the effect by Lee and Freely (2016) using robust Bayesian meta-analysis suggested publication bias in the literature and the need to revisit the phenomenon. We conducted a pre-registered far replication and extension of Studies 1 and 3 in Small et al. (2007), a seminal demonstration of the identifiable victim effect, with hypothetical donations. We examined the impact of deliberative thinking on the identifiable victim effect both by directly informing participants of the effect (Study 1) and by providing an identified victim with statistical information (Study 3). We found no empirical support for the identifiable victim effect (ηp2 = .000, 95% CI [.000, .003]) and subsequently no support for debiasing such a phenomenon (ηp2 = .001, 95% CI[.000, .012]). These findings suggest that the identifiable victim may be better framed in terms of ‘scope-insensitivity’. In other words, rather than providing more to a single identified victim, participants seem to be insensitive to the number of victims affected. However, our study involved only hypothetical donations rather than a real-effort real-donation paradigm as in Small et al. (2007). Therefore, we hope that our results spark motivation for future high-powered replications with real money donations, ideally carried out as registered reports and in collaboration with proponents of the original effect. Materials, data, and code were made available on the OSF: https://osf.io/n4jkh/ .

Publisher

University of California Press

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