Testing the “Zero‐Sum Game” Hypothesis: An Examination of School Health Policies and Practices and Inequalities in Educational Outcomes
Bibliographic record
Abstract
BACKGROUND: Health and education are intrinsically linked, while both are significantly patterned by socioeconomic status throughout the life course. Nevertheless, the impact of promoting health via schools on education is seen by some as a "zero-sum game"; ie, focusing resources on health improvement activity distracts schools from their core business of educating pupils, potentially compromising educational attainment. There is emerging evidence that school health improvement interventions may beneficially influence both health and attainment. However, few studies have examined the relationship between school health improvement activity and socioeconomic inequalities in educational attainment. METHODS: Wales-wide, school-level survey data on school health policies and practices was linked with routinely collected data on academic attainment. Primary outcomes included attendance and academic attainment at age 14 (Key Stage 3) and 16 (Key Stage 4). Linear regression models were constructed separately for high and low Free School Meal (FSM) schools, adjusting for confounders. Interaction terms were fitted to test whether there was an interaction between FSM, health improvement activity, and outcomes. RESULTS: There were positive associations between almost all school health variables and KS3 attainment among high, but not low FSM schools. Similarly, for attendance, there were positive associations of several health variables among high but not low FSM schools. There were no associations for KS4 attainment. CONCLUSIONS: Our findings did not support the "zero-sum game" hypothesis; in fact, among more deprived schools there was a tendency for better attendance and attainment at age 14 in schools with more embedded health improvement action.
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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 | 0.024 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".