A commentary on the Pan American Network of Nursing and Midwifery Collaborating Centres
Bibliographic record
Abstract
This article provides a commentary on the Pan American Network of Nursing and Midwifery Collaborating Centres (PANMCC). The objectives are to present an overview of the formation and evolution of the network, its impact on education, research, policy and communication and the benefits of membership. The advantages of international networks as a mechanism to strengthen nursing and midwifery workforces and improve health systems are also highlighted. The Pan American Health Organization (PAHO), the World Health Organization (WHO) Office in the Americas, oversees collaborating centres in the Region. Established in 1999, PANMCC consists of 17 centres situated in universities and schools of nursing. These centres provide crucial nursing and midwifery input to PAHO/WHO. The network supports global engagement and capacity building via collaboration, resource sharing and research colloquia. The linkages within the network enhance professional development, increase capacity building and heighten visibility of PANMCC and the work of its members.
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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 | 0.027 | 0.103 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.014 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.009 | 0.007 |
| Research integrity | 0.067 | 0.091 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".