Food services trends in New South Wales hospitals, 1993–2001
Bibliographic record
Abstract
Abstract A survey of the food service departments in 93 hospitals throughout NSW Australia (covering 51% of hospital beds in the state) was conducted using a mailed questionnaire and the results compared with those from similar surveys conducted in 1986 and 1993. Over the past eight years there has been a significant increase in the proportion of hospitals using cook‐chill food service production systems, from 18% in 1993 to 42% in 2001 (P < 0.001). Hospitals with cook‐chill systems had better staff ratios than those with cook‐fresh systems (8.3 vs. 6.4 beds/full time equivalent staff; p < 0.05), but there was no significant difference in the ratio of meals served per FTE. There was no difference between public and private hospitals in terms of ratios of beds or meals to food service staff. Managers using cook‐chill systems reported significantly lower levels of satisfaction with the food service system compared to those using cook‐fresh. Two aspects of the services have not changed since the last survey: approximately a quarter of food service departments are still managed by staff without formal qualifications and meal times remain the same, with more than 90% of hospitals serving the evening meal before 5.30 p.m. and a median of 14.25 h gap between the evening meal and breakfast.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".