Associations Between Vocational Interests and Personality “Beyond” the Big-Five
Bibliographic record
Abstract
This investigation explores the relationships between vocational interests and personality dimensions suggested to be “beyond” the Big Five or Five Factor Model. Participants (653 adults; 125 men and 528 women, with a mean age of 40.57 years, SD = 16.61, range 18–92) provided data on the 10 personality dimensions of the Supernumerary Personality Inventory (SPI; Paunonen, 2002), along with the 34 scales (27 work interests and seven work style preference scales) of the Jackson Career Inventory. Several significant associations, such as negative correlations between conventionality and an interest in the arts, negative correlations between femininity and an interest in science, positive correlations between humorous and an interest in nature/adventure/medicine, and positive correlations between manipulativeness and an interest in business were identified bringing to light new perspectives on how personality relates to different occupational roles and styles. The findings stress the importance of employing diverse personality and vocational interest measures to provide a more holistic view of associations between personality and career preferences. Limitations and future research are discussed.
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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 | 0.002 | 0.005 |
| 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 | 0.000 |
| 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".