Individual Differences in Identity Styles Predict Proactive Forms of Positive Adjustment
Bibliographic record
Abstract
The purpose of this study was to examine patterns of differences in proactive, adaptive forms of positive adjustment as a function of identity processing style. Three hundred undergraduate students (98 men, 202 women) completed self-report measures of identity styles (informational, normative, diffuse-avoidant), identity commitment, curiosity/exploration, proactive coping, and emotional intelligence. All three identity styles and identity commitment were found to be related to curiosity/exploration, proactive coping, and emotional intelligence. These relationships were positive with identity commitment and the informational and normative styles. When the overlapping variance accounted for by identity commitment was controlled via hierarchical regression, all three identity styles significantly predicted emotional intelligence, with positive predictions from the normative and informational styles. However, only the informational identity style made a unique positive contribution to curiosity/exploration and to proactive coping. These results are discussed in terms of the role of identity processing style in positive adjustment.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".