Association for Public Policy Analysis and Management
Bibliographic record
Abstract
provides supplemental foods, nutrition education, and social service and health care referrals to low-income pregnant, breastfeeding, and postpartum women, infants, and children up to age 5 who are at nutrition risk. The WIC program is based on the premise that many low-income individuals are at risk of poor nutrition and health outcomes because of insufficient nutrition during the critical growth and development periods of pregnancy, infancy, and early childhood. The WIC program is a supplemental food and nutrition program to help meet the special needs of low-income women, infants, and children during these periods. WIC began as a pilot program in 1972 and was authorized permanently in 1974 (P.L. 94-105). In the intervening 35 years, WIC has become a key component of the nutrition safety net provided for low-income Americans. Today, WIC functions as a vital link in America’s public health efforts to ensure that all of the nation’s children have the resources they need to thrive. More than half of all U.S. infants and a quarter of all U.S. children ages one to five receive WIC benefits. After 35 years, WIC is revising its food packages! The current WIC food packages have changed little since the early 1970s, yet significant changes have occurred in the demographic
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 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 | 0.011 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.237 | 0.122 |
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".