The 2 × 2 model of perfectionism: A comparison across Asian Canadians and European Canadians.
Bibliographic record
Abstract
The 2 × 2 model of perfectionism posits that the 4 within-person combinations of self-oriented and socially prescribed perfectionism (i.e., pure SOP, mixed perfectionism, pure SPP, and nonperfectionism) can be distinctively associated with psychological adjustment. This study examined whether the relationship between the 4 subtypes of perfectionism proposed in the 2 × 2 model (Gaudreau & Thompson, 2010) and academic outcomes (i.e., academic satisfaction and grade-point average [GPA]) differed across 2 sociocultural groups: Asian Canadians and European Canadians. A sample of 697 undergraduate students (23% Asian Canadians) completed self-report measures of dispositional perfectionism, academic satisfaction, and GPA. Results replicated most of the 2 × 2 model's hypotheses on ratings of GPA, thus supporting that nonperfectionism was associated with lower GPA than pure SOP (Hypothesis 1a) but with higher GPA than pure SPP (Hypothesis 2). Results also showed that mixed perfectionism was related to higher GPA than pure SPP (Hypothesis 3) but to similar levels as pure SOP, thus disproving Hypothesis 4. Furthermore, results provided evidence for cross-cultural differences in academic satisfaction. While all 4 hypotheses were supported among European Canadians, only Hypotheses 1a and 3 were supported among Asian Canadians. Future lines of research are discussed in light of the importance of acknowledging the role of culture when studying the influence of dispositional perfectionism on academic outcomes.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 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".