School start times and their association with rurality in British Columbia, Canada: An environmental scan
Bibliographic record
Abstract
Abstract Study Objectives Since later school start times are associated with increased sleep duration, our objectives were to identify mean school start times, the proportion of schools that start at 08:30 am or later, and determine if rurality was associated with school start times. Methods We conducted web searches for start times of 1759 standard schools in British Columbia (BC), Canada. Schools were categorized as elementary, elementary-middle, middle, middle-high, or high school and linked to an Index of Remoteness. We calculated descriptive statistics and used Analysis of Variance to assess for start time differences by grade category. We used Spearman’s rank-order correlation to assess if there was a relationship between start time and rurality. Results We found start times for 1553 (88.2%) of the included schools. The mean start time was 08:40 am (SD = 0:15) and ranged from 07:10 am to 09:45 am. There was a significant effect of grade category on start time, F (5, 1600) = 6.03, p < .001, η2 =.02, 95% CI [.006, .031] such that elementary-middle schools started significantly earlier (M = 08:34 am, SD = 0:17) than other grade categories. Overall, 1388 (86.4%) schools started at 08:30 am or later. Rurality was significantly correlated with school start time (r = −.198), such that more rural schools started earlier. Conclusions For the most part, school start times in BC meet recommendations that support childhood and adolescent sleep. Future research is needed to understand factors that promote the successful implementation of delayed school start times.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.011 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".