“Haram, she’s obese!” Young Lebanese-Canadian Women’s Discursive Constructions of “Obesity”
Bibliographic record
Abstract
Using feminist poststructuralist and postcolonial lenses, we explore how young Lebanese-Canadian women construct “obesity” within the context of the current and dramatic hype about “obesity” and its impacts on the health of individuals and populations. Participant-centered conversations were held with twenty young Lebanese-Canadian women between the ages of eighteen and twenty-five. In examining what discourses the participants adopted, negotiated, and/or resisted when discussing “obesity,” we found that the young women constructed it as a problematic health issue and a disease, as a matter of lack of discipline, and as an “abnormal” physical attribute. They also expressed feelings of disgust and/or pity toward “obese” women by using the Arabic term “haram” (what a shame or poor her). While the participants emphasized that Lebanese and Lebanese-Canadian cultures prize physical appearance and “not being fat,” they also attempted to dissociate themselves from “Lebanese” ways of thinking and, in doing so, reproduced a number of stereotypes about Lebanese, Lebanese-Canadian, and Canadian women.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".