Gender/sex disparity in self-reported sleep quality among Canadian adults
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: This study investigated gender differences in sleep quality among Canadian adults in a population-representative survey. METHODS: Data for this study was provided by the Canadian Community Health Survey (CCHS). For respondents (n = 39,700) who completed the 2011-12 CCHS sleep module, multinomial logistic regression investigated the relationship between gender and a composite sleep quality measure among adults ³18 years old, adjusted for confounders. RESULTS: Among the sample, gender was evenly distributed (49.3% men, 50.7% women). In the adjusted logistic model, female gender was independently associated with higher odds of poor sleep quality at all levels of poor sleep quality (from ‘a little of the time’ AOR=1.47, 95%CI:1.24, 1.73 to ‘all of the time’ AOR=2.10, 95%CI:1.74, 2.54). This disparity was progressively greater the more frequent the poor sleep quality reported for all but the highest poor sleep quality level. CONCLUSIONS: This study provides population-level evidence of a sleep quality disparity for Canadian women. Using a mixed gender population-based sample and a robust composite sleep quality measure, this study contributes to a growing understanding of poor sleep as a population health issue. Further research is needed to understand the mechanisms underlying this relationship, as well as to investigate effective public health and policy interventions for addressing sleep-gender population health disparities.
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.
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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it