An Individual Differences Measure of Attributions That Affect Achievement Behavior
Bibliographic record
Abstract
Attributing a negative achievement outcome (e.g., failing a test) to causes that are personally uncontrollable and stable elicits a low expectancy of future success, feelings of hopelessness in that domain, and reduced behavioral efforts to succeed. Thus, a tendency to make such attributions (i.e., dysfunctional academic attributional style) is an individual differences variable that puts people at risk. Two studies examine the factor structure and predictive validity of the Academic Attributional Style Questionnaire (AASQ). Study 1 (using two independent samples) found that the AASQ is a factorially valid measure of functional and dysfunctional attributional styles. In Study 2, during repeated failure in an academic task, the success expectancies, hopefulness, and behavioral persistence of students with a dysfunctional attributional style were lower than those of students with a functional attributional style. These findings modify the attributional theory of achievement motivation (Weiner, 1985) by positing an individual differences moderator variable (i.e., attributional style) and extend attributional research on at-risk students.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".