Bibliographic record
Abstract
Between 2004 and 2006, the Enhancing Interdisciplinary Collaboration in Primary Health Care (EICP) initiative undertook research on interdisciplinary collaboration. The last report prepared by the Initiative, Interdisciplinary Primary Health Care: Finding the Answers - A Case Study Report, offers a research-based blueprint for action by showcasing some current successful collaborative practices in primary health care. Several key learnings are discussed, especially in areas such as health human resources, funding, liability, regulation, information and communication technologies, management and leadership and planning and evaluation. Each of the primary health care organizations that were studied has created very different organizational cultures and teams. Each has faced different obstacles and developed innovative solutions to overcome them, indicating that there is no single right way, no step-by-step prescription as how to best pursue this method of care. Their innovative approaches are enlightening the way to interdisciplinary primary health care.
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 | 0.068 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.024 | 0.034 |
| Scholarly communication | 0.029 | 0.030 |
| Open science | 0.004 | 0.048 |
| Research integrity | 0.023 | 0.032 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".