45 research outputs found
Corruption and the Other(s): Scope of Superordinate Identity Matters for Corruption Permissibility
<div><p>The decision to engage in corruption—public and private corruption, nepotism, and embezzlement—is often attributed to rational actors maximizing benefits to themselves. However, the importance of reciprocal relationships in humans suggests that an actor may weigh the costs of harms of her corrupt behavior to individuals who may generate future benefits for her. We hypothesize that actors who have a larger circle of actual and potential social partners will have more individuals to consider when generating harms and will thus be less likely to find corrupt acts permissible than actors with smaller circles of valued others. Using data from the World Values Survey and European Values Study (WVS), we explore whether participants with a larger geographic identity or a greater number of group memberships (i.e. a larger scope of actual and potential social partners) are less likely to find accepting bribes permissible. We find mixed support for our hypotheses, but consistently find that WVS participants with local, country, continent, or world geographic identities are less likely to find accepting a bribe permissible than those with regional identities—that is, actors whose primary identities that encompass more than their region find corruption less permissible. We discuss the importance of considering an actor’s valuation of others when modeling corruption persistence, noting that establishing scopes of positive valuation is a precursor to predicting where actors will target benefits and shunt costs.</p></div
Number of group memberships and corruption permissibility<sup>1</sup>,<sup>2</sup>.
<p><sup>1</sup>Models with random country intercepts, country-level variables, or town population size (with country fixed effects) provide highly similar results, and so are not reported. Reported model n = 23,288.</p><p><sup>2</sup>AIC selection criteria suggest that the model including primary geographic identity provides a better fit than the model with only controls and resource shortfall variables (AIC<sub>in-group size</sub> = 0.99; AIC<sub>null</sub> = 22,277.93, AIC<sub>in-group size</sub> = 22,245.83).</p><p>Number of group memberships and corruption permissibility<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0144542#t004fn001" target="_blank"><sup>1</sup></a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0144542#t004fn002" target="_blank"><sup>2</sup></a>.</p
Primary geographic identity (baseline = local) and corruption permissibility<sup>1</sup>,<sup>2</sup>.
<p><sup>1</sup>Models with random country intercepts, country-level variables, or town population size (with country fixed effects) provide highly similar results, and so are not reported. Reported model n = 80,390. Country fixed effects not reported.</p><p><sup>2</sup>AIC selection criteria suggest that the model including primary geographic identity provides a better fit than the model with only controls (weighted AIC<sub>in-group size</sub> = 1; AIC<sub>null</sub> = 79,565.87, AIC<sub>in-group size</sub> = 79,489.08).</p><p><sup>3</sup>The intercept represents participants with regional identities, who had the lowest household resource shortfall, the lowest level of education, reported the lowest confidence in police and civil services, did not believe in God, had no children, were 0 years old, and male.</p><p>Primary geographic identity (baseline = local) and corruption permissibility<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0144542#t003fn001" target="_blank"><sup>1</sup></a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0144542#t003fn002" target="_blank"><sup>2</sup></a>.</p
Odds of finding corruption permissible with each additional membership in countries whose 95% CI >0.
<p>Odds of finding corruption permissible with each additional membership in countries whose 95% CI >0.</p
Proportion (box height) of participants with each primary geographic identity (box width) across 55 countries.
<p>“Cont.+” represents participants with a continent or world identity.</p
The distribution of participant's number of group identities across 22 countries.
<p>The distribution of participant's number of group identities across 22 countries.</p
Descriptive statistics for continuous variables.
<p>Descriptive statistics for continuous variables.</p
Odds of finding corruption permissible for three levels of primary geographic identity relative to regional identity.
<p>Odds of finding corruption permissible for three levels of primary geographic identity relative to regional identity.</p
Linear regression model of BMI on 319 adults aged 20+.
°<p><i>p</i><0.1,</p>*<p><i>p</i><0.05,</p>**<p><i>p</i><0.01,</p>***<p><i>p</i><0.001.</p
Mean physical activity ratio (PAR) by age and sex.
<p>Each data point represents one individual. PARs are derived from the factorial method, based only on observations from 7am–7pm (see text). The displayed curves are loess fits with 95% confidence intervals.</p