Organizing the Public Health-clinical Health Interface: Theoretical Bases
Bibliographic record
Abstract
This article addresses the issue of the interface between public health and clinical health within the context of the search for networking approaches geared to a more integrated delivery of health services. The articulation of an operative interface is complicated by the fact that the definition of networking modalities involves complex intra- and interdisciplinary and intra- and interorganizational systems across which a new transversal dynamics of intervention practices and exchanges between service structures must be established. A better understanding of the situation is reached by shedding light on the rationale underlying the organizational methods that form the bases of the interface between these two sectors of activity. The Quebec experience demonstrates that neither the structural-functionalist approach, which emphasizes remodelling establishment structures and functions as determinants of integration, nor the structural-constructivist approach, which prioritizes distinct fields of practice in public health and clinical health, adequately serves the purpose of networking and integration. Consequently, a theoretical reframing is imperative. In this regard, structuration theory, which fosters the simultaneous study of methods of inter-structure coordination and inter-actor cooperation, paves the way for a better understanding of the situation and, in turn, to the emergence of new integration possibilities.
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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 | 0.015 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.006 | 0.068 |
| Scholarly communication | 0.020 | 0.021 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".