État des lieux du financement des MRS et MRPA en Wallonie au travers d’une revue de la littérature: Mise en comparaison avec les structures françaises et canadiennes.
Bibliographic record
Abstract
Nous savons tous que le vieillissement de la population touche tous les pays du monde. Les gens vivant plus longtemps, une des conséquences à cette augmentation de longévité est la déclinaison de leur capacité physique et/ou cognitive. Le secteur des maisons de repos est donc amené à s’adapter pour pouvoir offrir une meilleure prise en charge de ces personnes vivant en institution de soins. Cette adaptation passe par un meilleur encadrement en termes de personnel, et donc un meilleur financement. Cette matière a été régionalisée depuis la 6ième Réforme de l’Etat. Ce présent mémoire se veut une présentation du financement des institutions pour personnes âgées qui se fera sous l’angle de la Wallonie, la France mais également du Québec, ce qui nous permettra d’établir une comparaison entre ces différents pays dans la première partie. La seconde partie reprendra la description de la méthodologie utilisée, ici en l’occurrence une revue de la littérature. Cette méthodologie a permis d’examiner un certain nombre de documents en utilisant une base de données connue. L’analyse a permis de mettre en exergue le rôle important des politiciens. De nombreux auteurs sont en demande d’un système de financement qui soit adapté à la situation réellement vécue par les acteurs de terrain ,équitable et surtout viable. Soulignons enfin la nouvelle tendance, qui peut être proposée comme une alternative ultime à la viabilité de ces institutions de soins pour personnes âgées, et qui est :« la désinstitutionalisation » de ces établissements et la priorisation des soins à domicile. Cette alternative a été évoquée à maintes reprises par plusieurs auteurs des trois pays étudiés. SummaryWe all know that population aging affects every country in the world. As people live longer, one of the consequences of this increase in longevity is the decline in their physical and/or cognitive capabilities. Therefore, the nursing home sector has got to adapt to be able to offer better care to the people living in care institutions. This adaptation requires better supervision in terms of personnel, and, accordingly, better funding. This matter has been regionalized since the 6th State Reform.The present thesis is intended to be a presentation of the funding of institutions for the elderly and will focus on the case of Wallonia, France but also of Quebec, which will allow us, in the first part, to establish a comparison between these different countries.The second part will serve to remind the definition of the methodology used, that is a review of literature on the subject. This methodology made it possible to examine a number of documents using a known database.The analysis highlighted the central role of politicians in this matter. Many authors are asking for a funding system that is adapted to the actual situation experienced by actors in the field, that is equitable and, more importantly, that is viable. We must also highlight the new trend, which can be proposed as an ultimate alternative to the viability of these care institutions for the elderly, which is “the deinstitutionalization” of these institutions and the prioritization of home care. This alternative has been mentioned many times by several authors from all three countries studied.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.015 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".