Autonomy regime in long term care arrangements : Instrumentation and territories
Bibliographic record
Abstract
The autonomy of people hampered by a disability, chronic illness, or functional loss involves individuals and the relatives or professionals who accompany them. It also concerns the institutional or organized players who debate, decide on, and implement support measures in this field. In France, as elsewhere in the world, changes in the relationship with autonomy through social policies are being driven by social factors such as population ageing, the transformation of family structure and of forms of employment, and political and historical factors that promote more or less individualized conceptions of autonomy (Börner, Bothfeld, Giraud, 2017). Changes are also taking place in specific practices of autonomy support. Since the mid-2000s, so-called “autonomy” policies in France have been aimed at people with disabilities and frail older people. In international debates, we speak of “long-term care (LTC) policies”. In France, and often abroad, these policies are still segmented according to the public, the nature of the services, and the functions. The notion of autonomy, in terms of LTC policies, is embodied in institutional and social arrangements. The Aurelia project aims to analyse autonomy regimes , which are defined as the organisational procedures for supporting autonomy among people with disabilities or frail older people. These emerge from social discourses, institutionalised norms, specific assistance measures, and the daily practices of carrying out support tasks. This project conducts a combined comparative analysis on the design of policy instruments (specialized debates, social discourses, and implementation procedures), the specific support practices for autonomy, and the different dimensions in which they are received by the concerned public and informal carers. This project will capture autonomy regimes at the territorial level in conjunction with national scales and individual situations. The Aurelia project develops three objectives: 1) analysis of the tensions between norms and practices of long-term care; 2) analysis of the tensions between national, territorial, and individual policies for regulating the provision of long-term care; and 3) a reading of the autonomy regimes through the analytical lens of instrumentation, as the instruments implement specific provisions and organise power relations in a given policy domain (capacities, financial resources, obligations, information, etc.). Specifically, the project focuses on the instruments for assessing autonomy loss, doctrines of rehabilitation, and tools that compensate for autonomy loss. In the case of those instruments, autonomy is simultaneously constructed by representations, scientific knowledge, and especially medical and professional knowledge. These instruments also give rise to the public’s acts of implementation and appropriation – or circumvention, whichever the case may be. The project analyses public discourses insofar as they contribute to defining the content of the notion of autonomy in long-term care policies, to forging policy instruments, and to structuring professional and lay knowledge corpuses that guide both the practices of implementing measures and informal acts of autonomy support that take place at home. Finally, the Aurelia project produces analyses of autonomy as a norm that is located at the intersection between individual expectations and differentiated social orders, which are driven by actors situated at various scales. The project is based on a pluralistic research methodology that comprises qualitative analyses of discourses, public policies (specifically instruments), interviews with actors involved in deciding on and implementing instruments as well as with informal actors, and recipients of the various measures and autonomy support practices. The quantitative analysis will capture the disparities between territories and characterise the autonomy regimes in specific contexts: equipment, policy implementation and take up, varieties in the modes of care, socio-economic indicators, and the configurations of actors and care practices at the beneficiary level. The Aurelia project is based on an international and multidisciplinary research consortium. In France, specialists in sociology, political science, geography, demography, law, public health, economics and medicine are organised into five teams: INED, LISE-CNAM CNRS, EHESP, EHESS, and IRES. The members of these different teams have already achieved successful scientific work and are experienced in comparative analysis. The Aurelia consortium's partner teams in Germany, Canada, Japan, and the United Kingdom are leaders in their fields. Furthermore, productive partnerships have already been tested among the consortium members.
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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 | 0.013 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.006 | 0.037 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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 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".