The Relationship of Parents’ Perfectionism with Academic Self-Regulation and Self-Control
Bibliographic record
Abstract
The present study aimed to examine the relationship of parents’ perfectionism with academic self-regulation and self-control among male high school students in Iranshahr. This descriptive study followed a correlational design. The statistical population included all third grade second period male high school students in Iranshahr and the sample included 140 individuals selected hierarchically among 235 individuals using Morgan’s table. To collect data, the Frost Multidimensional Perfectionism Scale (1990), the Ryan and Connell Academic Self-Regulation (1989), and the Weinberger and Schwartz Self-Restraint Scale (1990) were applied. The obtained data was analyzed using Pearson correlation coefficient and stepwise regression analysis. The results indicated that parents’ perfectionism, parents’ expectations, and individual standards were significantly and negatively related to academic self-regulation. Among components of perfectionism, parents’ expectations explained 6% of the variance in academic self-regulation. Moreover, parents’ perfectionism and concerns about mistakes, parents’ expectations, and individual standards were significantly and negatively correlated with students’ self-regulation. When explaining self-control via components of parents’ perfectionism, in the first step, individual standards alone explained 19% of the variance in students’ self-control. In the second step, component of concerns about mistakes together with individual standards explained 27% of the variance in students’ academic self-regulation. Additionally, in the third step, component of parents’ expectations along with individual standards and concerns about mistakes explained 32% of the variance in students’ self-control.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".