The Meaning of Dining: The Social Organization of Food in Long-term Care
Bibliographic record
Abstract
OBJECTIVE: To explore the social organization of food provision in publicly funded and regulated long-term care facilities. METHODS: Observations were conducted, along with 90 interviews with residents, families, and health providers in two Southern Ontario sites using rapid site-switching ethnography within a feminist political economy framework as part of an international, interdisciplinary study investigating healthy ageing. RESULTS: Food is purchased within a daily $7.80/per resident allotment, limiting high quality choices, which is further problematized by privatization of food services. Funding restrictions also result in low staffing levels, creating tensions in aligning with other Ministry mandated tasks such as bathing, and documenting: competing demands often lead to rushed meals. Regulations, primarily set in response to scandals and to ensure appropriate measured nutrition, reinforce the problem. Further, regulations regarding set meal times result in lack of resident agency, which is compounded by fixed menu options and seating arrangements in one common dining room. Rather than being viewed as an important part of resident socialization, food is reduced to a medicalized task, organized within a climate of cost-containment. IMPLICATIONS: Findings warrant Ministry financial support for additional staff and for food provision. Policy changes are also required to give primacy to this population's quality of life.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.017 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".