Implementation of functional autonomy measurement system: barriers and facilitators in PISE-Dordogne project
Bibliographic record
Abstract
OBJECTIVES: The objectives of the study were to identify the adjustments made during the implantation and the conditions favouring or limiting the SMAF utilisation. METHODS: A multiqualitative quote was developed. The Functional autonomy measurement system (SMAF) was implanted in 11 French medico-social establishments. Analyses were made with the mixed type thematic method from Miles and Huberman. RESULTS: Principal adjustments that have been made during implantation concern the informatics assistance and clinical support. Strategic, organizational and individual factors explained adhesion level of actors and the subsequent flow of implantation. CONCLUSION: Establishment of SMAF and of the software eSMAF® in the medico-social establishments rests on a certain number of conditions which could be identified during the study. These conditions made it possible to work out structured recommendations for future implementations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".