Document Type

Article

Publication Date

12-2022

Abstract

Could cooperation among strangers be facilitated by adaptations that use sparse information to accurately predict cooperative behaviour? We hypothesize that predictions are influenced by beliefs, descriptions, appearance, and behavioural history available for first and second impressions. We also hypothesize that predictions improve when more information is available. We conducted a two-part study. First, we recorded thin-slice videos of university students just before their choices in a repeated Prisoner’s Dilemma with matched partners. Second, a worldwide sample of raters evaluated each player using either videos, photos, only gender labels, or neither images nor labels. Raters guessed players’ first-round Prisoner’s Dilemma choices and then their second-round choices after reviewing first-round behavioural histories. Our design allows us to investigate incremental effects of gender, appearance, and behavioural history gleaned during first and second impressions. Predictions become more accurate and better-than-chance when either gender, appearance, or behavioural history are added. However, these effects were not incrementally cumulative. Predictions from treatments showing player appearance were no more accurate than from treatments revealing gender labels and predictions from videos were no more accurate than from photos. These results demonstrate how people accurately predict cooperation under sparse information conditions, helping explain why conditional cooperation is common among strangers.

Comments

ESI Working Paper 22-19

Previously titled "Predictive Mind Reading from First and Second Impressions: Better-than-chance Prediction of Cooperative Behavior"

This article later underwent peer review and was published as:

Schniter, E., & Shields, T. W. (2024). Predictive mind reading from first and second impressions: Better-than-chance prediction of cooperative behavior. Evolutionary Human Sciences, 6, e2. https://doi.org/10.1017/ehs.2023.30

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.