A Commentary on the Relationship between Self-efficacy, Problem-focused Coping and Performance
Bibliographic record
Abstract
Self-efficacy influences self-regulatory cognition and behaviour, including the way we approach and cope with problems and how we perform tasks. In this paper I examined the construct of self-efficacy and the strongly related variables of coping and performance to better understand how self-efficacy works at a fundamental level. I briefly reviewed some key concepts, measures and methods used in the study of self-efficacy, commenting on potentially important and understudied differences in coping styles that may influence self-efficacy. Specifically, problem-focused coping was the main coping strategy in the literature that had a positive correlation with both self-efficacy and performance. Lastly, I present some ideas for future research toward more understanding of the development of self-efficacy and its contributing factors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.058 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.008 | 0.003 |
| Research integrity | 0.048 | 0.057 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".