Network formation, governance, and evolution in public health
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Collaborative networks of health organizations have received a great deal of attention in recent years as a way of enhancing the flow of information and coordination of services. However, relatively little is known about how such networks are formed and evolve, especially outside a local, community-based setting. This article is an in-depth discussion of the evolution of the North American Quitline Consortium (NAQC). The NAQC is a network of U.S. and Canadian organizations that provide telephone-based counseling and related services to people trying to quit smoking. METHODOLOGY: The research draws on data from interviews, documents, and a survey of NAQC members to assess how the network emerged, became formalized, and effectively governed. FINDINGS: The findings provide an understanding of how multiregional public health networks evolve, while building on and extending the broader literature on organizational networks in other sectors and settings. Specifically, we found that the network form that ultimately emerged was a product of the back-and-forth interplay between the internal needs and goals of those organizations that would ultimately become network members, in this case, state-, and provincial-level tobacco quitline organizations. We also found that network formation, and then governance through a network administrative organization, was driven by important events and shifts in the external environment, including the impact and influence of major national organizations. PRACTICE IMPLICATIONS: The results of the study provide health care leaders and policy officials an understanding of how the activities of a large number of organizations having a common health goal, but spanning multiple states and countries, might be coordinated and integrated through the establishment of a formal network.
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.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it