Trajectories of Body Mass and Self-Concept in Black and White Girls
Bibliographic record
Abstract
As a stigmatizing condition, obesity may lead to the internalization of devalued labels and threats to self-concept. Modified labeling theory suggests that the effects of stigma may outlive direct manifestations of the discredited characteristic itself. This article considers whether obesity's effects on self-concept linger when obese youth enter the normal body mass range. Using longitudinal data from the National Growth and Health Study on 2,206 black and white girls, we estimated a parallel-process growth mixture model of body mass linked to growth models of body image discrepancy and self-esteem. We found that discrepancy was higher and self-esteem lower in formerly obese girls compared to girls always in the normal range and comparable to chronically obese girls. Neither body image discrepancy nor self-esteem rebounded in white girls despite reduction in body mass, suggesting that the effects of stigma linger. Self-esteem, but not discrepancy, did rebound in black girls.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".