Overcoming adversity: The protective role of locus of control, attributional style, and self-efficacy, in the promotion of resilience.
Bibliographic record
Abstract
One main purpose of the present study was to investigate the ability of internal locus of control, optimistic attributional style, and high self-efficacy to serve as protective factors, buffering the negative impact of life stressors (both number of negative life events and daily hassles) on current competence (overall, as well as in the academic, social, and emotional domains). Given that an examination of protective factors presupposes that life stressors actually constitute risk factors for maladjustment, another related purpose was to examine this relationship directly, to determine whether such an assumption is justified. The present results suggest that the influence of daily hassles may be greater than that of past life events. Thus, it may be more important to search for factors that promote resilience in the face of more minor, ongoing stressors. Of the possible protective factors, self-efficacy, consistently emerged as a more powerful and consistent predictor of current competence than attributional style and locus of control, and was the best predictor of both social and overall competence. (Abstract shortened by UMI.)Dept. of Psychology. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2002 .G86. Source: Masters Abstracts International, Volume: 41-04, page: 1204. Adviser: Stewart Page. Thesis (M.A.)--University of Windsor (Canada), 2002.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".