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Successful businesses today are attending to internal and external
changes. Their leaders value diversity and seek a heterogeneous
workforce, recognising that effective work teams are essential in the
process. In the shaping and managing of new organisational cultures,
consultants can provide assistance. This article describes a Fortune 50
company client where a particular method of team‐building was used that
involved the results of a five‐month consultation which included 20
subgroups in eight cities.

Erik Angner has argued that simultaneous endorsement of the representational theory of measurement (RTM) and psychometrics leads to inconsistency. His claim rests on an implicit assumption: RTM and psychometrics are full-fledged approaches to measurement. I argue that RTM and psychometrics are only partial approaches that deal with different aspects of measurement, and that therefore simultaneous endorsement of the two is not inconsistent. The argument has implications for the improvement of measurement practices.

The current age of 'austerity' is associated with neoliberal ideology. Neoliberalism can be understood as a form of governmentality – a way of reconfiguring selves and the social order in accord with the demands of market economies. A recent UK policy initiative by the Coalition government's Behavioural Insights Team required benefit claimants to submit to online psychometric testing. We examine this policy in some detail, arguing that this use of psychometric testing is flawed, unethical, and unlikely to help claimants to find work. Our analysis of the test procedure and its results suggests that the policy functions primarily as a means whereby benefit claimants can be 'nudged' towards acceptance of the precepts of neoliberal subjectivities.

The period 1895–1925 saw the origins and establishment of the fields that came to be called econometrics and psychometrics. I consider what these fields owed to biometry—the statistical approach to the biological problems of evolution—and make some comparisons between all three. I emphasize developments in biology and psychology, for these are less familiar to historians of econometrics. These developments are interesting to contemplate, for the biometricians and psychometricians were already discussing issues associated with the respective roles of statistical analysis and of subject matter theory, issues that became prominent in econometrics only much later.

A statement from Michell (Michell, J., "Normal science, pathological science, and psychometrics",Theory and Psychology, Vol. 10 No. 5, 2000, pp. 639‐67), "psychometrics is a pathology of science", is contrasted with conventional definitions provided by leading texts. The key to understanding why Michell has made such a statement is bound up in the definition of measurement that characterises quantification of variables within the natural sciences. By describing the key features of quantitative measurement, and contrasting these with current psychometric practice, it is argued that Michell is correct in his assertion. Three avenues of investigation would seem to follow from this position, each of which, it is suggested, will gradually replace current psychometric test theory, principles, and properties. The first attempts to construct variables that can be demonstrated empirically to possess a quantitative structure. The second proceeds on the basis of using qualitative (non‐quantitatively structured) variable structures and procedures. The third, applied numerics, is an applied methodology whose sole aim is pragmatic utility; it is similar in some respects to current psychometric procedures except that "test theory" can be discarded in favour of simpler tests of observational reliability and validity. Examples are presented of what future practice may look like in each of these areas. It is to be hoped that psychometrics begins to concern itself more with the logic of its measurement, rather than the ever‐increasing complexity of its numerical and statistical operations.

PurposeDue to the paucity of research on web-based job applicant screening (i.e. cybervetting), the purpose of the current study was to examine the psychometric properties of cybervetting, including an examination of the impact of adding structure to the rating process.Design/methodology/approachUsing a mixed-factorial design, 122 supervisors conducted cybervetting evaluations of applicant personality, cognitive ability, written communication skills, professionalism, and overall suitability. Cross-method agreement (i.e. the degree of similarity between cybervetting ratings and other assessment methods), as well as interrater reliability and agreement were examined, and unstructured versus structured cybervetting rating formats were compared.FindingsCybervetting assessments demonstrated high interrater reliability and interrater agreement, but only limited evidence of cross-method agreement was provided. In addition, adding structure to the cybervetting process did not enhance the psychometric properties of this assessment technique.Practical implicationsThis study highlighted that whereas cybervetting raters demonstrated a high degree of consensus in cybervetting-based attributions, there may be concerns regarding assessment accuracy, as cybervetting-based ratings generally differed from applicant test scores and self-assessment ratings. Thus, employers should use caution when utilizing this pre-employment screening technique.Originality/valueWhereas previous research has suggested that cybervetting ratings demonstrate convergence with other traditional assessments (albeit with relatively small effects), these correlational links do not provide information regarding cross-method agreement or method interchangeability. Thus, this study bridges a crucial gap in the literature by examining cross-method agreement for a variety of job-relevant constructs, as well as empirically testing the impact of adding structure to the cybervetting rating process.

This project incorporates two steps. First, the psychometric model of risk perception is evaluated for its validity under field conditions. Second, individuals are classified as risk amplifiers or attenuators and the characteristics of those groups are explored. Survey data from an ongoing case study is employed in the analysis. The case study involves a Midwestern community in which a controversy exists over the possibility of the existence of a cancer cluster caused by the operation of a small reactor. Results show that the psychometric model of risk perception, while failing to be reproduced precisely, does has utility under the field conditions in this study. Use of the psychometric model to classify individuals as risk amplifiers or risk attenuators produces a useful dichotomy that reveals differences between the two polar groups in terms of demographics, satisfaction with institutional response to the risk, concern over individual and social levels of risk, and the evaluation of various communication channels as having been useful in coming to a judgment about the risk. A final model comparing the two groups suggests that, in this case, evaluation of personal risk and satisfaction with institutional response are important determinants of individual's risk reactions. Subordinate to these forces are the demographic variables of education, gender, and years of residence in the community. The model also illustrates that aggregate‐level observations may not be representative of subgroups.

AbstractThe present study aimed to develop and validate a checklist questionnaire addressing career problems faced by college students. The research involved four steps: scale development, exploratory factor analysis, scale revision, and confirmatory factor analysis and correlation analyses. The career problem checklist comprised four components with 16 items: Self‐awareness (4 items), Occupational Information (4 items), Career Decision‐making (4 items), and Job‐seeking Skills (4 items). The reliability and the validity of the current scale were supported by the high levels of coherence of the subscales and their correlations with the related measures. The study's limitations and implications are also discussed.