The longitudinal associations between perfectionism and academic achievement across adolescence
Bibliographic record
Abstract
The directionality and longitudinal course between perfectionism and academic achievement throughout adolescence remains unclear as most studies rely on cross-sectional or short-term data and many examine these associations in university students who do not represent the full spectrum of learners. Moreover, most studies are hampered by their reliance on student-reported grades. We rectified these issues by examining the longitudinal relation between self-reported perfectionism and teacher-rated academic achievement (grade point average) in a sample of 604 Canadian adolescents followed prospectively from Grade 7 to Grade 12. Using path analysis, results demonstrated a positive relation between academic achievement and perfectionism. In particular, academic achievement positively predicted self-oriented perfectionism (SOP) at every time point. Academic achievement also positively predicted socially prescribed perfectionism across every time point. At no time point did either form of perfectionism predict academic achievement, highlighting that perfectionism is more likely an outcome of academic achievement, rather than an antecedent. Results also demonstrated that the cross-lagged effect from academic achievement to SOP was stronger at the transition from middle school to high school compared to pathways in all subsequent years. Overall, such findings imply that adolescents who experience academic success are more likely to experience increases in levels of perfectionism, which may increase their vulnerability to stress.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".