Improving the Life Chances of Vulnerable Children and Families with Prenatal and Infancy Support of Parents: The Nurse-Family Partnership*
Bibliographic record
Abstract
Pregnancy and the early years of the child's life offer an opportune time to prevent a host of adverse maternal and child outcomes that are important in their own right, but that also have significant implications for the development of criminal behavior. This paper summarizes a three-decade program of research that has attempted to improve the health and development of mothers and infants and their future life prospects with prenatal and infancy home visiting by nurses. The program, known as the Nurse-Family Partnership, is designed for low-income mothers who have had no previous live births. The home visiting nurses have three major goals: to improve the outcomes of pregnancy by helping women improve their prenatal health; to improve the child’s health and development by helping parents provide more sensitive and competent care of the child; and to improve parental life-course by helping parents plan future pregnancies, complete their educations, and find work. Given consistent effects on prenatal health behaviors, parental care of the child, child abuse and neglect, child health and development, maternal life-course, and criminal involvement of the mothers and children, the program is now being offered for public investment throughout the United States, where careful attention is being given to ensuring that the program is being conducted in accordance with the program model tested in the randomized trials. The program also is being adapted, developed, and tested in countries outside of the US: the Netherlands, England, Scotland, Northern Ireland, Australia, and Canada, as well as Native American and Alaskan Native populations in the US, where programmatic adjustments are being made to accommodate different populations served and health and human service contexts. We believe it is important to test this program in randomized controlled trials in these new settings before it is offered for public investment.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".