Testing Effects of Community Collaboration on Rates of Low Infant Birthweight at the County Level
Bibliographic record
Abstract
Interorganizational collaboration has become a popular strategy for addressing population health and well-being. However, evidence for its effectiveness in achieving outcomes at the population level is limited, at least in part due to a variety of methodological challenges such as reduced sample size at the population level, the availability of suitable comparison groups of communities, and study durations that are too short to detect slowly emerging outcomes. The present study addresses these challenges by retrospectively examining the effectiveness of a mature network of community collaboratives, using latent growth modeling of longitudinal change in an archival community-level outcome, low infant birthweight, and propensity score matching of comparison communities. A group of 25 Georgia counties with collaboratives targeting low infant birthweight was compared to a weighted comparison group of counties from other southeastern states, using propensity score matching. We report results of full matching methods and outcome analyses examining differences in change in county rates of low infant birthweight from 1997 to 2004 between intervention and comparison counties. Results indicated significantly smaller increases in low weight birth rates in intervention counties than in comparison counties.
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".