La médiation dans les soins de santé : enjeux et perspectives
Bibliographic record
Abstract
Entitled “Mediation in the Healthcare sector: challenges and perspectives”, the doctoral research focuses on mediation in the context of the healthcare relationship regulated in Belgium by the Act of August 22nd, 2002 on Patient’s Rights. It also contains indications on the way this type of mediation has been regulated in France, in the Netherlands and in Quebec.\nThe research begins with a study of the concept of mediation, its principles and objectives, along with a comparison between the applications of mediation in the different fields of Belgian law (criminal law, public law, family law, etc.). A critical and constructive analysis of existing and proposed regulations on mediation in the healthcare sector in the four aforementioned legal systems is then carried out, with a special attention to the mediators’ perception on these regulations and their daily practice.\nIn this context, the research aims to answer several fundamental questions: what are the specificities of healthcare mediation in comparison with other fields of mediation application? Given these specificities, what kind of model for the process of mediation and the statute of mediators could be suggested as a general standard for the patient-physician relationship, beneath the particular regulations in force in the legal systems?\nOnce this model has been constructed, the legal framework for healthcare mediation in Belgium, as regulated in the Act of August 22nd, 2002 on Patient’s Rights, has to be questioned: does it suit to the specificity of the healthcare sector? Which improvements could be made in order to strive towards the proposed model of mediation and of the mediator’s statute?
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.022 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| 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".