Self-esteem and persistence in the face of failure.
Bibliographic record
Abstract
In 2 studies, the authors examined self-esteem, persistence, and rumination in the face of failure. Study 1 manipulated degree of failure and availability of goal alternatives. When an alternative was available, high self-esteem (HSE) participants persisted more than low self-esteem (LSE) participants after a single failure, but less after repeated failure. When no alternative was available, no self-esteem differences in persistence emerged. LSE participants ruminated more than HSE participants. Study 2 examined persistence and rumination for 10 personal goals across an academic year. HSE participants were better calibrated (higher within-subject correlations between perceived progress and persistence across goals), had higher overall levels of persistence, higher grade point averages, and lower levels of rumination than LSE participants. Although traditional views that emphasize the tenacious persistence of HSE individuals need revision, HSE people appear more effective in self-regulating goal-directed behavior.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".