A Model Infant Feeding Policy for Baby-Friendly Designation in the USA
Bibliographic record
Abstract
BACKGROUND: In June 2010, the Communities Putting Prevention to Work program (Centers for Disease Control and Prevention) funded a New Jersey (NJ) Office on Nutrition and Fitness, Department of Health and Senior Services project to reduce obesity and increase exclusive breastfeeding by increased implementation of the Baby-Friendly Hospital Initiative in the state of NJ. At baseline, NJ had no Baby-Friendly hospitals and no hospital was using an infant feeding policy that conformed to standards required by Baby-Friendly USA for designation. GOAL: To create a model infant feeding policy that would be adaptable for use at multiple NJ hospitals preparing for Baby-Friendly designation. METHODS: Project consultants created a policy based on existent policies from the American Academy of Pediatrics, the Academy of Breastfeeding Medicine, certified Baby-Friendly hospitals, and guidance from Baby-Friendly USA. This policy was submitted to Baby-Friendly USA, the US body responsible for Baby-Friendly designation. RESULTS: Baby-Friendly USA requested changes; after adaptations, the policy was made available to targeted NJ hospitals via a statewide portal. The hospitals made relevant adaptations for their setting, and those that were ready submitted the policy during the Baby-Friendly designation process. The policy was acceptable to Baby-Friendly USA. CONCLUSION: A collaborative initiative can use a single breastfeeding policy template as an aid toward Baby-Friendly designation. Such work streamlines the process and saves time and resources.
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.
How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".