Being a ‘good mother’: Dietary governmentality in the family food practices of three ethnocultural groups in Canada
Bibliographic record
Abstract
In this qualitative study with three ethnocultural groups in two regions of Canada, we explore how official dietary guidelines provide particular standards concerning 'healthy eating' that marginalize other understandings of the relationship between food and health. In families where parents and youth held shared ways of understanding healthy eating, the role of 'good mother' was constructed so as to include healthy eating expertise. Mothers expressed a perceived need to be personally responsible for providing skills and knowledge about healthy eating as well as guarding children against negative nutritional influences. Governing of family eating practices to conform to official nutritional advice occurred through information provision, monitoring in shopping and meal preparation, restricting and guiding food purchases, and directly translating expert knowledges into family food practices. In families where parents and youth held differing understandings of healthy eating, primarily families from ethnocultural minority groups, mothers often did not employ the particular western-originating strategies of conveying healthy eating information, or mentoring healthy meal preparation, nor did they regulate or restrict children's food consumption. Western dietary guidelines entered into the family primarily through the youth, emphasizing the nutritional properties of food, often devaluing 'traditional' knowledge about healthy eating. These processes exemplify techniques of governmentality which simultaneously exercise control over people's behaviour through normalizing some family food practices and marginalizing others.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.025 | 0.011 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".