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Title: Workplace gender discrimination and the implicit association test
Author: Kandola, Jo-Anne
ISNI:       0000 0004 5370 7907
Awarding Body: Aston University
Current Institution: Aston University
Date of Award: 2015
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Women are under-represented at senior levels within organisations. They also fare less well than their male counterparts in reward and career opportunities. Attitudes toward women in the workplace are thought to underpin these disparities and more and more organisations are introducing attitude measures into diversity and inclusion initiatives to: 1) raise awareness amongst employees of implicit attitudes, 2) educate employees on how these attitudes can influence behaviour and 3) re-measure the attitude after an intervention to assess whether the attitude has changed. The Implicit Association Test (IAT: Greenwald, et al., 1998) is the most popular tool used to assess attitudes. However, questions over the predictive validity of the measure have been raised and the evidence for the real world impact of the implicit attitudes is limited (Blanton et al., 2009; Landy, 2008; Tetlock & Mitchell, 2009; Wax, 2010). Whilst there is growing research in the area of race, little research has explored the ability of the IAT to predict gender discrimination. This thesis addresses this important gap in the literature. Three empirical studies were conducted. The first study explored whether gender IATs were predictive of personnel decisions that favour men and whether affect- and cognition-based gender IATs were equally predictive of behaviour. The second two studies explored the predictive validity of the IAT in comparison to an explicit measure of one type of gender attitude, benevolent sexism. The results revealed implicit gender attitudes were strongly held. However, they did not consistently predict behaviour across the studies. Overall, the results suggest that the IAT may only predict workplace gender discrimination in a very select set of circumstances. The attitude component that an IAT assesses, the personnel decision and participant demographics all impact the predictive validity of the tool. The interplay between the IAT and behaviour therefore appears to be more complex than is assumed.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available