Development of Interventions to Support Provincial Implementation of the Baby-Friendly Initiative: A Study Protocol
Bibliographic record
Abstract
Breastfeeding is internationally recognized as the optimal form of infant nutrition. The Baby-Friendly Initiative (BFI) is an evidence-informed program that leads to improved breastfeeding outcomes. Despite the benefits of breastfeeding, Nova Scotia has one of the lowest breastfeeding rates in Canada. Additionally, only two birthing hospitals in the province have BFI designation. We aim to address this gap using a sequential qualitative descriptive design across three phases. In Phase 1, we will identify barriers and facilitators to BFI implementation through individual, semi-structured interviews with 40 health care professionals and 20 parents. An analysis of relevant policy and practice documents will complement these data. In Phase 2, we will develop implementation interventions aimed at addressing the barriers and facilitators identified in Phase 1. An advisory committee of 10-12 administrative, clinical, and parent partners will review these interventions. In Phase 3, the interventions will be reviewed by a panel of 10 experts in BFI implementation through an online survey. Feedback on the revised implementation interventions will then be sought from 20 health system and parent partners through interviews. This work will use implementation science methods to support integrated and sustained implementation of the BFI across hospital/community and rural/urban settings in Nova Scotia. This study was not registered.
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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 | 0.076 | 0.043 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.046 | 0.007 |
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".