Affective forecasting and ex-offender hiring decisions

Abstract

With over 600,000 Americans released from jails and prisons each year, it is increasingly important to understand the challenges that ex-offenders face when they attempt to reintegrate into society. Prior recidivism data indicate that over 80% of this population were rearrested within a decade of release, suggesting that the current social and economic environment is not conducive to successful reentry. The current research employs a simulation paradigm to explore how affective forecasting might predict hiring decisions for applicants with a criminal history. Using an online sample of adults (N = 322), an experimental hiring paradigm examined mock employment decisions for Black versus White applicants with or without a criminal history by measuring the degree to which applicant characteristics determined mock employer emotional forecasts and how those forecasts subsequently mediated simulated hiring outcomes. As expected, mock employers forecasted more intense negative emotion and less intense positive emotion when considering applicants who had a criminal history, and those forecasts predicted less favorable mock hiring outcomes for ex-offender applicants. Additionally, consistent with affective forecasting research, results showed that participants over-estimated the intensity of their negative emotion by forecasting more intense negative feelings than they experienced upon learning about the simulated hiring outcome. These findings suggest that evaluators generate emotional expectations about hiring applicants with a criminal history, which in turn account for their employment recommendations. Further, when evaluators utilize negative emotional predictions in a hiring decision they are likely relying on inaccurate information.