Does the School Performance Variable Used in the International Health Behavior in School‐Aged Children (HBSC) Study Reflect Students' School Grades?
Bibliographic record
Abstract
BACKGROUND: Given the pressure that educators and policy makers are under to achieve academic standards for students, understanding the relationship of academic success to various aspects of health is important. The international Health Behavior in School-Aged Children (HBSC) questionnaire, being used in 41 countries with different school and grading systems, has contained an item assessing perceived school performance (PSP) since 1986. Whereas the test-retest reliability of this item has been reported previously, we determined its convergent and discriminant validity. METHODS: This cross-sectional study used anonymous self-report data from Austrian (N = 266), Norwegian (N = 240), and Canadian (N = 9,717) samples. Students were between 10 and 17 years old. PSP responses were compared to the self-reported average school grades in 6 subjects (Austria) or 8 subjects (Norway), respectively, or to a general, 5-category-based appraisal of most recent school grades (Canada). RESULTS: Correlations between PSP and self-reported average school grade scores were between 0.51 and 0.65, representing large effect sizes. Differences between the median school grades in the 4 categories of the PSP item were statistically significant in all 3 samples. The PSP item showed predominantly small associations with some randomly selected HBSC items or scales designed to measure different concepts. CONCLUSIONS: The PSP item seems to be a valid and useful question that can distinguish groups of respondents that get good grades at school from those that do not. The meaning of PSP may be context-specific and may have different connotations across student populations from different countries with different school systems.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".