Navigating academic setbacks with intention and self-efficacy for decentering and self-compassion
Bibliographic record
Abstract
After setbacks, students want to regain their balance. One way to do this is by keeping a healthy distance from disturbing cognitive and emotional experiences (decentering) and being kind to oneself (self-compassion). The present work pioneers assessing the intention and self-efficacy for decentering and self-compassion after academic setbacks on a comprehensive international sample across four studies ( N = 1846). We propose distinguishing between intention and self-efficacy, as students may desire to engage in decentering and self-compassion following setbacks (intention), but they may not believe they can do so (self-efficacy). Study 1 suggests that the post-setback decentering and self-compassion dimensions have strong reliability and are well separated regarding both the intention and self-efficacy constructs. Intention and self-efficacy had weak-to-moderate correlations, indicating the relevance of the distinct constructs. Study 2a and Study 2b demonstrated that both constructs have meaningful relationships with constructs related to well-being and mental health in the academic context but are independent of academic performance. Study 2c demonstrated a meaningful relationship pattern with growth mindset and mindset meaning system measures. Students' post-setback intentions and self-efficacy for decentering and self-compassion seem relevant for their well-being during academic challenges but not for their academic performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".