Psychometric Characteristics of a Public-Domain Self-Report Measure of Vocational Interests: The Oregon Vocational Interest Scales
Bibliographic record
Abstract
We investigated the psychometric properties of the Oregon Vocational Interest Scales (ORVIS), a brief public-domain alternative to commercial inventories, in a large community sample and in a college sample. In both samples, we examined the factor structure, scale intercorrelations, and personality correlates of the ORVIS, and in the community sample, we also examined the correlations of the ORVIS scales with cognitive abilities and with the scales of a longer, proprietary interest survey. In both samples, all 8 scales-Leadership, Organization, Altruism, Creativity, Analysis, Producing, Adventuring, and Erudition-showed wide variation in scores, high internal-consistency reliabilities, and a pattern of high convergent and low discriminant correlations with the scales of the proprietary interest survey. Overall, the results support the construct validity of the scales, which are recommended for use in research on vocational interests and other individual differences.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".