Applicant, assessor, and selection method factors related to ethnic score differences in police officer selection

1. Applicant, assessor, and selection method factors related to ethnic score differences in police officer selection Marise Ph. Born and Lonneke A.L. de Meijer Erasmus University Rotterdam The Netherlands Hans van Loon Police Academy of The Netherlands Henk T. van der Molen Erasmus University Rotterdam The Netherlands born@fsw.eur.nl 28th International Congress of Psychology, Beijing, 8-13 August 2004 28th ICP

2. Overview • Score differences on objective and subjective measures • Objective: cognitive tests and self-report personality tests; no interference of an assessor/ interviewer • Subjective: interference of an assessor or interviewer • Selection procedure at the Dutch police • Overview of findings and comparison with literature • Possible explanations for subjective measures from the perspective of • Assumed-characteristics theory • Complexity-extremity theory • Demographic similarity framework • Concluding remarks

3. Selection procedure at the Dutch police • National selection for 28 police forces • Selection measures • Cognitive ability test and Personality test • Assessment Center and Interview • Final selection advice • Data • 12,609 applicants; 1,481 ethnic minority applicants; approx 20 assessors/ interviewers involved • Ethnic groups • Largest ethnic minority groups in The Netherlands: Antilleans, Moroccans, Surinamese, and Turks. Dutch white majority group

4. Score differences between min. and maj. groups Note. Positive d values indicate the ethnic majority group scores higher

5. Integrating these results • The ethnic majority group is scoring higher on almost all selection measures • One exception: Conscientiousness (d’s between -.50 and -.30). • Differences between ethnic minority group and ethnic majority group decrease from first- to second generation: • The most for Antilleans • The least for Turks

6. Explaining score differences on subjective measures • Explanations abundant in cognitive domain • In personality domain, findings seem unsystematic and explanations therefore do not make sense • For subjective measures: • How do assessors’/ interviewers’ perceptions of an applicant influence their evaluations? • First, two social psychological frameworks; only tested in the laboratory until now. • Then, demographic similarity perspective.

7. Assumed-characteristics theory (ACT) • Theory as follows (Coleman et al., 1995; Jussim et al., 1987): Based on knowledge about certain demographics of a group, people make assumptions about other characteristics of this group. Example: Knowledge of ethnicity -> assumption of certain SES, certain personality In-group characteristics will be more favorably perceived; but more, relevant, demographic information on out-group will decrease unfavorable assumed characteristics -> evaluations of out-group members more positive. • Hypothesis therefore: Applicant demographics, namely Dutch language-proficiency and education, will explain more of the variability in evaluations than ethnicity itself explains variability in evaluations

8. ACT results

9. Complexity-Extremity Theory (CET) • Theory as follows (Coleman et al., 1995; Jussim et al., 1987): • A complex representation of someone will lead to less extreme evaluations (in-group members), and a simple representation leads to more extreme evaluations (out-group members) • Hypotheses therefore: • Ethnic majority raters will evaluate ethnic minority applicants with a high Dutch language-proficiency and education higher than ethnic majority applicants with the same Dutch-language-proficiency and education • Ethnic majorities evaluate ethnic minority applicants with a low Dutch language-proficiency and education lower than ethnic majority applicants with the same Dutch-language-proficiency and education

10. CET results for high Dutch language-proficiency and education

11. CET results for low Dutch language-proficiency and education

12. Demographic similarity • Hypothesis: the more demographically similar the applicant is to the rater (gender, ethnicity, age...) the higher the evaluation will be (e.g., Sacco et al., 2003). • Preliminary results show support for this framework. Multivariate analyses of variance: Ethnic score differences were found on each of the subjective measures. These were accounted for by several instances of demographic (dis)similarities. For example: • Interview: Some significant differences found: Older male (ethnic majority) interviewers rate ethnic minority males quite low (3.0) and male majority candidates high (4.8) (on 7-point scale with sd’s of 1).

13. Concluding remarks • Score differences on all selection measures between the ethnic majority group and second-generation minorities are smaller than between the majority group and first-generation minorities. • In support of assumed-characteristics theory, Dutch language-proficiency and education explain more of the variability in score differences than ethnicity does. • Extremity-complexity theory seems to be unsupported: a general tendency exists to rate ethnic minorities a bit lower than the ethnic majority, although effect sizes are small. • Demographic similarity framework promising; need to also look into perceived similarity framework.