The main elements in the design and validation of personnel selection procedures have been in place for many years. The role of job analysis, contemporary models of work performance and criteria are reviewed critically. After identifying some important issues and reviewing research work on attracting applicants, including applicant perceptions of personnel selection processes, the research on major personnel selection methods is reviewed. Recent work on cognitive ability has confirmed the good criterion‐related validity, but problems of adverse impact remain. Work on personality is progressing beyond studies designed simply to explore the criterion‐related validity of personality. Interview and assessment centre research is reviewed, and recent studies indicating the key constructs measured by both are discussed. In both cases, one of the key constructs measured seems to be generally cognitive ability. Biodata validity and the processes used to develop biodata instruments are also critically reviewed. The article concludes with a critical evaluation of the processes for obtaining validity evidence (primarily from meta‐analyses) and the limitations of the current state of the art. Speculative future prospects are briefly reviewed.

This is the second of two articles that address recent scholarship about teaching and learning about evolution. This second review seeks to summarize this state of affairs and address the implications of this work for the classroom by addressing four basic questions: (1) What is evolution?/What components of the theory are important at the introductory level? (2) Why do students and members of the public at large need to understand evolution? (3) What makes evolution difficult to teach and learn? and (4) What promising instructional approaches have been developed and tested? The paper will also focus on concerns about both the research designs and the measures used in this work. Based on this review, I will then propose a set of pedagogical implications and recommendations for the classroom instructor and call for studies to address specific gaps identified.

The present study reports the development of a brief, quantitative, web-based, psychometrically sound measure-the Generalized Acceptance of EvolutioN Evaluation (GAENE, pronounced "gene") in a format that is useful in large and small groups, in research, and in classroom settings. The measure was designed to measure only evolution acceptance-not related knowledge or religious beliefs. Item development was based on extensive student interviews and pretesting followed by multiple rounds of qualitative review and quantitative validity testing based on expert review (Lawshe, 1975) and multiple rounds of item revision, then by reliability testing of over 600 high school (HS) and post-secondary (PS) students (Study 1, GAENE 1.0). Data analysis strongly supported the reliability and validity of GAENE 1.0, principal components analysis supported a two-factor solution. All the negatively worded items (and only those items) loaded on the second factor. Rasch analysis also suggested the need for items that would be endorsed at the lower end of the person-item scale. The negatively worded items were, therefore, reworded as positives, additional items were generated to attract wider endorsement, two additional rounds of qualitative and quantitative expert validation were conducted, and reliability testing was repeated with over 600 HS and PS students (Study 2, GAENE 2.0). Both reliability and validity indices of GAENE 2.0 were strong (Lawshe content validity index ¼ 0.72; Cronbach's alpha HS ¼ 0.940; Cronbach's alpha PS ¼ 0.948; Cronbach's alphacombined ¼ 0.945). Principal components analysis suggests that GAENE 2.0 measures a single factor. Together with Rasch analysis results, these data provide substantial initial evidence to support the validity and psychometric integrity of the GAENE as a measure of the degree to which high school and college students accept the theory of evolution. The rigorous development process can also serve as a model for others interested in measure development. #

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By a theorem due to Sklar, a multivariate distribution can be represented in terms of its underlying margins by binding them together using a copula function. By exploiting this representation, the "copula approach" to modelling proceeds by specifying distributions for each margin and a copula function. In this paper, a number of families of copula functions are given, with attention focusing on those that fall within the Archimedean class. Members of this class of copulas are shown to be rich in various distributional attributes that are desired when modelling. The paper then proceeds by applying the copula approach to construct models for data that may suffer from selectivity bias. The models examined are the self-selection model, the switching regime model and the double-selection model. It is shown that when models are constructed using copulas from the Archimedean class, the resulting expressions for the log-likelihood and score facilitate maximum likelihood estimation. The literature on selectivity modelling is almost exclusively based on multivariate normal specifications. The copula approach permits selection modelling based on multivariate non-normality. Examples of self-selection models for labour supply and for duration of hospitalization illustrate the application of the copula approach to modelling. Copyright Royal Economic Society, 2003