A Social-Belonging Intervention Benefits Higher Weight Students’ Weight Stability and Academic Achievement
Bibliographic record
Abstract
Psychological interventions can narrow college achievement gaps between students from nonstigmatized and stigmatized groups. However, no intervention we know of has investigated effects for one highly stigmatized group: people of higher bodyweights. We analyzed data from a prematriculation social-belonging intervention trial at 22 colleges, which conveyed that adversity in the college transition is normative, temporary, and nondiagnostic of lack of belonging. Nine months postintervention, higher weight participants in a standard belonging treatment had higher first-year grade point averages (GPAs) than controls and maintained more stable weights, an indicator of physical well-being. Effects of a belonging treatment customized to specific colleges were directionally similar but nonsignificant. Exploratory analyses revealed that effects did not differ by race and that weight effects were driven by women. Together, results show that higher weight students contend with belonging concerns that contribute to a weight gap in GPA, but belonging interventions can raise GPA and promote healthy weight stability.
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How this classification was reachedexpand
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 | 0.004 | 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 | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".