Diabetes awareness and body size perceptions of Cree schoolchildren
Bibliographic record
Abstract
Native American Indians and First Nations are predisposed to obesity and diabetes. A study was done to understand Cree schoolchildren's diabetes awareness and body size perceptions in two communities that had diabetes awareness-raising activities in the Province of Quebec, Canada. Children (N = 203) in grades 4-6 were classified into weight categories using measured heights and weights and grouped on diabetes awareness based on dichotomous responses to the question 'Do you know what diabetes is?' Children selected a drawing of an American Indian child whom they felt most likely to get diabetes and described their body size perception using a closed response question. Although 64.5% of children were overweight or obese, most (60.1%) children considered their body size to be 'just right', with 29.6% considering it 'too big' and 10.3% considering it 'too small'. A minority (27.6%) of children had diabetes awareness. These children were more likely than children without diabetes awareness to consider their body size too big (42.9 versus 24.5%) and to choose an obese drawing as at risk for diabetes (85.7 versus 63.3%, odds ratio 3.48 and 95% confidence interval 1.53-7.91). Culturally appropriate health education programs to increase schoolchildren's diabetes awareness and possibility to have a healthy body weight are important.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".