The Search is on for Coherent Performance Measurement in Healthcare Organizations. Has Quebec Reached a Crossroads
Bibliographic record
Abstract
Objective: This research looks back at a 10-year period (2004–2014) to understand the development and outlook for healthcare organization performance measurement in the Quebec healthcare system, in an attempt to objectivize relationships within the configuration of its principal institutional actors. Methods: This is a qualitative study combining the use of official publications and fieldwork based on 13 semi-directed interviews, conducted in 2014, with informers in key performance measurement positions within the Quebec healthcare system. Results: Performance measurement has generated tensions, both internally between different branches of the Department of Health and externally against a strong coalition of external institutional actors, which were defending a shared homogeneous vision of performance. Four major types of political power plays, owing to the power struggles around performance models and indicators, converged around the same implicit issue of the need to attain greater legitimacy in order to impose an authoritative frame of reference.
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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 | 0.030 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.013 |
| Science and technology studies | 0.010 | 0.012 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".