The determinants of successful collaboration: A review of theoretical and empirical studies
Bibliographic record
Abstract
Successful collaboration in health care teams can be attributed to numerous elements, including processes at work in interpersonal relationships within the team (the interactional determinants), conditions within the organization (the organizational determinants), and the organization's environment (the systemic determinants). Through a review of the literature, this article presents a tabulated compilation of each of these determinant types as identified by empirical research and identifies the main characteristics of these determinants according to the conceptual work. We then present a "showcase" of recent Canadian policy initiatives--The Canadian Health Transition Fund (HTF)--to illustrate how the various categories of determinants can be mobilized. The literature review reveals that very little of the empirical work has dealt with determinants of interprofessional collaboration in health, particularly its organizational and systemic determinants. Furthermore, our overview of experience at the Canadian HTF suggests that a systemic approach should be adopted in evaluative research on the determinants of effective collaborative practice.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.008 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".