Examining risk factors for overweight and obesity in children with disabilities: a commentary on Bronfenbrenner’s ecological systems framework
Bibliographic record
Abstract
Globally, overweight and obesity (OW/OB) levels are high among children, with rates surpassing the adult population. With such high pediatric OW/OB rates, it is imperative that risk factors are identified and explored. Thus, Davison and Birch developed an adapted framework, based on Bronfenbrenner's Ecological Systems Theory, which identifies and categorizes the factors in a child's life that put them at risk for OW/OB. While a socioecological perspective has been a useful tool for examining risk factors in typically developing pediatric populations, this holistic approach has not yet been applied to populations of children with disabilities, who are at an even higher risk of OW/OB than their typically developing peers. This commentary, therefore, explores Bronfenbrenner's Ecological Framework as applied to OW/OB by Davison and Birch, and critically examines its application to children with disabilities.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".