Eating disorders symptomatology: Comparative study between Mexican and Canadian university females / Sintomatología de trastornos alimentarios: Estudio comparativo entre mujeres universitarias mexicanas y canadienses
Bibliographic record
Abstract
The objectives of this study were: (1) to compare Mexican and Canadian university\nstudents regarding disordered eating behaviors (DEB), body thin-ideal internalization (BTHIN),\nand body image dissatisfaction (BID); and (2) to examine the relationship of these three variables\nto body mass index (BMI) and waist circumference (WC). This cross-cultural study was carried\nout in a sample of 129 university women students aged from 18 to 25 years (M = 20.18, SD = 1.59):\n52% were Canadian (Moncton University [MU]) and 48% were Mexican (Universidad Autónoma\ndel Estado de Hidalgo [UAEH]). The Brief Questionnaire for Disordered Eating Behaviors and\nAttitudes Towards Body Figure Questionnaire were applied while the BID was evaluated using a\ncontinuum of nine silhouettes. In addition, the weight, height and WC of each participant were\nrecorded. Mexican students had greater values of overweight, obesity, abdominal obesity and\nDEB, with 4.6 times greater risk than UM students. In contrast, the presence of BTHIN and BID\nwas similar between samples. Considering these findings, women from at least two different\nethnic groups are vulnerable to the development of eating disorder symptomatology.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".