Risk perception, regulation, and unlicensed child care: lessons from Ontario, Canada
Bibliographic record
Abstract
In 2014, the Province of Ontario, Canada undertook a number of legislative changes regarding child care. Part way through the process, a series of tragic focusing events occurred: a number of infants and children died in unlicensed child care over a short period of time. Despite these events, the Province chose to allow a portion of the family child care (FCC) sector to remain unlicensed and essentially unregulated in a sector that is otherwise subject to strict licensing and regulation. Drawing on research on risk regulation, we analyse FCC regulation in comparison to other sectors and find that FCC is surprisingly under-regulated, given the health and safety risks. Legislative debate analysis reveals a number of rationales for non-regulation. In addition to pragmatic political concerns such as costs associated with licensing, analysis reveals concerns about choice and accessibility over quality and safety. We conclude with a call for a research agenda to further examine parents’ and policy-makers’ perceptions of risk.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".