Cognitive predictors and age-based adverse impact among business executives.
Bibliographic record
Abstract
Age differences on measures of general mental ability and specific cognitive abilities were examined in 2 samples of job applicants to executive positions as well as a mix of executive/nonexecutive positions to determine which predictors might lead to age-based adverse impact in making selection and advancement decisions. Generalizability of the pattern of findings was also investigated in 2 samples from the general adult population. Age was negatively related to general mental ability, with older executives scoring lower than younger executives. For specific ability components, the direction and magnitude of age differences depended on the specific ability in question. Older executives scored higher on verbal ability, a measure most often associated with crystallized intelligence. This finding generalized across samples examined in this study. Also, consistent with findings that fluid abilities decline with age, older executives scored somewhat lower on figural reasoning than younger executives, and much lower on a letter series test of inductive reasoning. Other measures of inductive reasoning, such as Raven's Advanced Progressive Matrices, also showed similar age group mean differences across settings. Implications for employee selection and adverse impact on older job candidates are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".