From goal motivation to goal progress: the mediating role of coping in the Self-Concordance Model
Bibliographic record
Abstract
The present studies examined the mediating role of self-regulatory mechanisms in the relationship between goal motivation and goal progress in the Self-Concordance Model. First, a systematic review, using meta-analytical path analysis, supported the mediating role of effort and action planning in the positive association between autonomous goal motivation and goal progress. Second, results from two additional empirical studies, using structural equation modeling, lent credence to the mediating role of coping in the relationship between goal motivation and goal progress of university students. Autonomous goal motivation was positively associated with task-oriented coping, which predicted greater goal progress during midterm exams (Study 1, N=702) and at the end of the semester in a different sample (Study 2, N=167). Controlled goal motivation was associated with greater disengagement-oriented coping (Study 1 and Study 2) and lesser use of task-oriented coping (Study 2), which reduced goal progress. These results held up after controlling for perceived stress (Study 2). Our findings highlight the importance of coping in the "inception-to-attainment" goal process because autonomous goal motivation indirectly rather than directly predicts goal progress of university students through their usage of task-oriented coping.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".