Evaluating case studies of community-oriented integrated care
Bibliographic record
Abstract
This paper summarises a ten-year conversation within London Journal of Primary Care about the nature of community-oriented integrated care (COIC) and how to develop and evaluate it. COIC means integration of efforts for combined disease-treatment and health-enhancement at local, community level. COIC is similar to the World Health Organisation concept of a Community-Based Coordinating Hub - both require a local geographic area where different organisations align their activities for whole system integration and develop local communities for health. COIC is a necessary part of an integrated system for health and care because it enables multiple insights into 'wicked problems', and multiple services to integrate their activities for people with complex conditions, at the same time helping everyone to collaborate for the health of the local population. The conversation concludes seven aspects of COIC that warrant further attention.
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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 | 0.057 | 0.098 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.006 | 0.014 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".