Sex Differences in Vocational Interests
Bibliographic record
Abstract
Abstract In this chapter, we examine sex differences in vocational interests over generations and cohorts. Utilizing a large sample of adults (N = 1,774) who completed the Jackson Career Explorer (JCE), men scored significantly higher on the mathematics, physical science, engineering, adventure, dominant leadership, finance, sales, law, and professional advising interest scales. Women scored significantly higher on the creative arts, social science, personal service, teaching, social service, elementary education, family activity, and office work, interest scales as well as the work styles of stamina, accountability, and planfulness. To examine if sex differences in vocational interests have changed over time, sex differences for two editions of the Jackson Vocational Interest Survey manuals were compared. Surprisingly, few differences were found. In contrast, when the JCE responses were analyzed by age cohorts, sex differences do appear to be slightly smaller in the younger sample, suggesting that further analyses are required with successive generations.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".