An investigation of the personality traits of scientists versus nonscientists and their relationship with career satisfaction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Drawing on H olland's vocational theory, S chneider's A ttraction‐ S election‐ A ttrition model, and the B ig F ive/narrow traits model of personality, the present study identified key B ig F ive and narrow personality traits that both distinguish scientists from members of other occupations and related these to their career satisfaction. A sample of 2,015 scientists had significantly higher levels of openness, intrinsic motivation, and tough‐mindedness, and significantly lower levels of assertiveness, conscientiousness, emotional stability, extraversion, optimism, and visionary style than a sample of nonscientists ( n = 78,753). Seven traits were significantly correlated with the career satisfaction of scientists: agreeableness/teamwork, assertiveness, emotional stability, extraversion, openness, optimism, and work drive. Based on these results, a psychological profile of scientists was presented. Findings were discussed in terms of the functional value and person–occupation fit of these traits for the work of scientists. Implications were described for the recruitment, selection, management, and promotion of scientists, as well as their training, development, coaching, counseling, and mentoring.
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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 | 0.000 | 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 it