Weight Measurements in School: Setting and Student Comfort
Bibliographic record
Abstract
OBJECTIVE: To examine how body mass index assessments are conducted in schools and whether student comfort with assessments varies by students' perceived weight status, weight satisfaction, or privacy during measurements. METHODS: In-person cross-sectional surveys with diverse fourth- to eighth-grade students (n = 11,510) in 54 California schools in 2014-2015 about their experience being weighed in the prior school year. RESULTS: Half of the students (49%) reported being weighed by a physical education teacher and 28% by a school nurse. Students were more comfortable being weighed by nurses than physical education teachers (P = 0.01). Only 30% of students reported privacy during measurements. Students who were unhappy with their weight (P <0.001) and those who perceived themselves as overweight (P <0.001) were less comfortable being weighed than their peers. CONCLUSIONS AND IMPLICATIONS: Student weight dissatisfaction, higher perceived weight status, and being female were associated with discomfort with school-based weight measurements. Prioritizing school nurses to conduct weight measurements could mitigate student discomfort, and particular attention should be paid to students who are unhappy with their weight to avoid weight stigmatization.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".