Health of caregivers in child care
Bibliographic record
Abstract
BACKGROUND: Child care workers play an important role in caring for children attending child care yet there is little research regarding their health. METHODS: The study consisted of focus groups with child care workers and a survey, conducted as part of a larger study known as the Healthy Child Care Study, which focused on children. The study investigated carers working in formal child care [long day care (LDC) and family day care (FDC)]. RESULTS: Questionnaires to caregivers in centres showed that 86% had taken sick leave in the previous year and 75% of staff had taken leave for infectious illness. Carers in FDC reported that 24% had taken sick leave in the previous year and 12% of carers had taken leave for infectious illness. Of responding caregivers from centres, 22% were cigarette smokers while in FDC homes, 8% of carers smoked. In focus groups, carers reported that their major areas of health concern were stress, infectious illness and physical trauma such as lifting injuries. CONCLUSIONS: Child care workers in LDC took more sick leave than those in FDC but this is not necessarily due to more illness. Child care workers are a diverse and important group that require further research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".