A Systematic Review of Teachers’ Causal Attributions: Prevalence, Correlates, and Consequences
Bibliographic record
Abstract
The current review provides an overview of published research on teachers' causal attributions since 1970s in the context of theoretical assumptions outlined in Weiner's (2010) attribution theory. Results across 79 studies are first examined with respect to the prevalence of teachers' interpersonal causal attributions for student performance and misbehavior, as well as intrapersonal attributions for occupational stress. Second, findings showing significant relations between teachers' attributions and their emotions and cognitions, as well as student outcomes, are discussed. Third, an overview of results showing the prevalence and implications of teachers' causal attributions to be moderated by critical background variables is also provided. Finally, observed themes across study findings are highlighted with respect to the fundamental attribution error and the utility of Weiner's attribution theory for understanding how teachers' explanations for classroom stressors impact their instruction, well-being, and student development.
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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 | 0.015 | 0.103 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".