Is the PRISMA-France glass half-full or half-empty? The emergence and management of polarized views regarding an integrative change process
Bibliographic record
Abstract
AIM: The PRISMA-France pilot project is aimed at implementing an innovative case management type integration model in the 20th district of Paris. This paper apprehends the emergence of two polarized views regarding the progression of the model's spread in order to analyze the change management enacted during the process and its effects. METHOD: A qualitative analysis was conducted based on an institutional change model. RESULTS: Our results suggest that, according to one view, the path followed to reach the study's current level of progress was efficient and necessary to lay the foundation of a new health and social services system while according to the other, change management shortcomings were responsible for the lack of progress. DISCUSSION: While neither of these two views appears entirely justified, analyzing the factors underlying their differences pinpoints some of the challenges involved in managing the spread of an integrated service delivery network. Meticulous preparation for the change management role and communication of the time and effort required for a wholesale institutional change process may be significant factors for a successful integrative endeavor.
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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 | 0.042 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.028 |
| Scholarly communication | 0.018 | 0.016 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".