authors ’ affiliations Correspondence to:
Bibliographic record
Abstract
Aims: To investigate the characteristics of parent–infant bed-sharing prevalence in England. Methods: Data on night-time sleeping practices from a two year, local, longitudinal study and a three-year, national, cross-sectional study were obtained. A total of 261 infants in North Tees were followed up at 1 and 3 months of age, as were 1095 infants aged 1 week to 1 year from five English health regions. Results: Data from both studies found that almost half of all neonates bed-shared at some time with their parents (local = 47%, 95 % CI 41 to 54; national = 46%, 95 % CI 34 to 58), and on any one night in the first month over a quarter of parents slept with their baby (local = 27%, 95 % CI 22 to 33; national = 30%, 95% CI 20 to 42). Bed-sharing was not related to younger mothers, single mothers, or larger families, and was not more common in the colder months, at weekends, or among the more socially deprived families; in fact bed-sharing was more common among the least deprived in the first months of life. Breast feeding was strongly associated with bed-sharing, both at birth and at 3 months. Bed-sharing prevalence was uniform with infant age from 3 to 12 months; on any one night over a fifth of parents (national = 21%, 95 % CI 18 to 24) slept with their infants. Conclusion: Bed-sharing is a relatively common practice in England, not specific to class, but strongly related to breast feeding.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.696 | 0.297 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".