Perfectionism dimensions and research productivity in psychology professors: Implications for understanding the (mal)adaptiveness of perfectionism.
Bibliographic record
Abstract
The consequences of demanding perfection of oneself are hotly debated, with researchers typically arguing for either the adaptiveness or the maladaptiveness of this trait. Research informing this debate involves mainly psychiatric patients, undergraduates, and self-report data, suggesting a need to broaden this relatively narrow evidence base. The present study examines self-oriented perfectionism (i.e., demanding perfection of oneself), conscientiousness, socially prescribed perfectionism, neuroticism, and research productivity in psychology professors. Self-oriented perfectionism was negatively related to total number of publications, number of first-authored publications, number of citations, and journal impact rating, even after controlling for competing predictors (e.g., conscientiousness). Self-oriented perfectionism may represent a form of counterproductive overstriving that limits research productivity amongst psychology professors. Although self-oriented perfectionism is often labeled as adaptive, such statements may be overly general.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| 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".