Study aimed at identifying factors with the potential to reduce the disparities in mathematics anxiety observed between 15-year-old French-speaking boys and girls in Quebec, based on an analysis of PISA data from 2003 and 2012
Bibliographic record
Abstract
A previous study (Vohl & Loye, 2023) showed that, on average, 15-year-old French-speaking Quebec girls are more anxious about mathematics than French-speaking Quebec boys across the performance continuum. The results also showed that performances in mathematics and mathematics anxiety are two negatively correlated phenomena. This paper aims to identify factors that could explain the differences in mathematics anxiety observed between girls and boys and that may have the potential to reduce the observed differences. The Pekrun’s control-value model for achievement emotions (2006) was used to verify whether differences in self-concept, intrinsic value, and utility value observed between girls and boys completely explain the differences in mathematical anxiety. The results in self-concept explain nearly 70% of the differences in mathematics anxiety observed among francophone students in Quebec.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".