1986
DOI: 10.1111/j.1744-6570.1986.tb00584.x
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Sex Bias in Job Evaluation Procedures

Abstract: Issues pertaining to possible sex bias in job evaluation procedures are outlined and relevant research pertaining to these issues reviewed. Attention is given to possible sex bias in job analysis procedures, choice and weighting of factors, reliability and validity issues, and other concerns. Future research needs are discussed, with particular attention being paid to the reliability and validity aspects of job evaluation instruments.

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Cited by 45 publications
(36 citation statements)
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“…This reinforces the need for additional research into the various inputs into pay decisions, such as job evaluation (see Arvey, 1986) and market surveys (Rynes & Milkovich, 1986).…”
Section: Discussionmentioning
confidence: 99%
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“…This reinforces the need for additional research into the various inputs into pay decisions, such as job evaluation (see Arvey, 1986) and market surveys (Rynes & Milkovich, 1986).…”
Section: Discussionmentioning
confidence: 99%
“…Although some might argue that our manipulation was too subtle, we believe this to be a less significant problem than gender obtrusiveness in an era of heightened sensitivity to comparable worth. Moreover, many of the biases discussed in the job evaluation literature are indeed very subtle, and hypothesized to operate with only minimal gender cues (see Arvey, 1986;McArthur, 1985 Rater Sex (Dummy) .88 .11 * Significant at p < .01…”
Section: Discussionmentioning
confidence: 99%
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“…In this manner, one can reasonably conclude that these predictors contribute to explaining salary and are not due to chance. Various approaches using multiple regression include the Salary Kit method (Gray and Scott, 1980;Scott, 1977), the Oaxaca method (Oaxaca, 1973), reverse regression (Birnbaum, 1985;Conway and Roberts, 1986), compa-ratio analysis (Bereman and Scott, 1991), and differential regression (Arvey, 1986;Taylor, 1988). These various regression approaches differ along a number of dimensions, including (a) specification of predictor and criterion variables, (b) modeling specifications, and (c) the evidence or criteria used to determine the presence or absence of pay discrimination (Moore, 1993).…”
mentioning
confidence: 99%