Similarities and differences in social and emotional profiles among students in Canada, USA, China, and Singapore: PISA 2015
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although previous research showed that discrete social-emotional skills such as empathy, motivation, and social relationships in school significantly predict achievement, students tend to use various social-emotional skills in combination. As such previous investigations cannot comment on how different combinations or profiles of students’ social-emotional skills predict achievement relative to discrete skills. Likewise, little is known about cross-national comparisons of social-emotional skill profiles (SESP), and the extent to which SESP differ on their academic achievement. The purposes of this study were three-folded: 1) to determine whether a four-factor social-emotional skills model could be used for cross-national comparisons; 2) to identify social-emotional profiles in 15-year-old students from four different countries – Canada, the United States, China, and Singapore; and 3) to evaluate how different profiles predict students’ reading, maths, and collaborative problem-solving (CPS) test scores. Our results showed multigroup measurement invariant in the structure, loadings, and thresholds of the four-factor social-emotional skills model. We identified three profiles labelled Sociable, Reserved and Withdrawn in Canada, Singapore, and the United States; whereas, we found three profiles labelled Solitary, Team-oriented, and Reserved in students in China. Finally, the way each profile associated with reading, maths and CPS in each country appeared to align with the cultural expectations of learning.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it