SOCIAL IDENTITY THEORY & SIMILARITY ATTRACTION PARADIGM

1. An Investigation of Race and Sex Similarity Effects in Assessment Centers in the South African context.Christine de VilliersMasters Supervisor: Francois de Kock15 March 2011Department of Industrial PsychologyUniversity of Stellenbosch

2. SOCIAL IDENTITY THEORY &SIMILARITY ATTRACTION PARADIGM • The assessor plays a critical role in the evaluation process. However the evaluations made by the assessors are subjective and therefore susceptible to intentional and unintentional biases (Mount, Sytsma, Hazucha, & Holt, 1997). • There are multiple environmental and cognitive variables that influences the accuracy of the inferences made by assessors and heighten the probability of similarity judgements in assessment centres (Lowry, 1993; Sagie & Magnezy, 1997; Lievens 2002; Sacco, Scheu, Ryan & Schmitt, 2003).

3. SOCIAL IDENTITY THEORY &SIMILARITY ATTRACTION PARADIGM • Social identity theory: By striving to maintain a consistent identity individuals tend to evaluate others with similar characteristics more favourable than individuals with dissimilar characteristics (Sacco, Scheu, Rayn, & Schmitt, 2003; Goldberg, 2005). • Both sex and race similarities have been found to influence work and employee related judgments in employee evaluation (Schmidt, 1976; Oppler, White, & Borman,1989; Lin, Dobbins and Fahr, 1992; Graves and Powell, 1995; Goldberg, 2005; Purkiss, Perrewe, Gillespie, Mayes and Ferris, 2006 Dean, Bobko, & Roth, 2008)

4. Similarity in evaluations • Gender similarities effects have been found by various reserchers; Oppler, White and Borman (1989) found significant interactions as well as main effects for gender similarities in the performance appraisal context. Graves and Powell (1995) found that interviewers found members of the opposite sex more similar to themselves, although it affected only marginally higher rating. Goldberg (2005) also found that there is a sex-dissimilarity effect amongst male raters that indicated their preferences female applicants. Dean, Bobko and Roth (2008) in their Meta-analysis found that on average females get higher ratings than males in assessment centres. • There are also several studies that have found race similarity effects in the evaluation context. Schmidt (1976) found that racial and attitudinal similarity was related to higher ratings. Pulakos, Oppler, White and Borman (1989) found significant interactions as well as main effects for race similarities in the performance appraisal. In 1997 Mount et al, in their study on performance ratings, found that Blacks gave more favourable ratings to all employees of their own race. Goldberg (2005) found a significant race-similarity effect for white raters.

5. Similarity in evaluations • Therefore, it could be expected that Rater schema and similarity bias can influence the ratings in assessment centres. Similarity bias have been confirmed in other contexts, e.g. interviews (Graves et. Al., 1995) and performance appraisal ratings (Oppler et. al.,1989 ). • However Little is known about possible demographic similarity effects in AC ratings.

6. RESEARCH QUESTION AND RESEARCH OBJECTIVES • Research Question Social identity theory suggests that demographic similarity in rater-ratee dyads could bias assessor ratings. Does assessor-assessee similarity influence AC dimension scores, so that assessors assign higher dimension ratings to individuals that are demographically similar to themselves? • Objectives • To determine if rater and ratee demography act as main effects on AC PEDR; • To determine if rater-ratee demographic similarity acts as interaction effects in AC PEDR.

7. HYPOTHESES • Main effects for Rater (Assessor) and Ratees (Candidates) will be investigated prior to determining whether rater-ratee interaction effects exist. However, no hypotheses will be formulated a priori about main effects due to the fact that the South African context differs markedly from the US context, bringing into question the generalisability of these findings. • Interaction effects of Rater (Assessor) and Ratee (Assessee) Race H3: Raters will rate same-race ratees higher than other ratees(Same-race positive bias). Or: same race bias will not occur/same race negative bias will occur. • Interaction effects of Rater (Assessor) and Ratee (Assessee) Sex H1: Raters will rate same-sex ratees higher than they rate other ratees (Same-sex positive bias). Or: same sex bias will not occur/same sex negative bias will occur.

8. METHOD • Client identity and all client data will be kept anonymous. • Hope to partner with an existing AC where the demographics of both the assessors and assessees are available. • Would be ideal to have a sample of +-100 candidates evaluated by at least five raters. • Will use HLM analysis like in Sacco, Scheu, Rayn, & Schmitt (2003) to test for interaction and main effect.

9. IMPLICATIONS • To ensure that selection and evaluation is unbiased and does not discriminate against any individual based on demographic characteristics one must identify and remove or minimise any factors that contribute to error variance in selection procedures. • If the Similarity dyads have a significant impact on dimension ratings then one can look at ways to improve the process to so increase the validity of the assessment centre process