Do Assessment Tools Shape Policy Preferences? Analysing Policy Framing Effects on Older Adults’ Conceptualisation of Autonomy
Bibliographic record
Abstract
Abstract The concept of autonomy is essential in the practice and study of gerontology and in long-term care policies. For older adults with expanding care needs, scores from tightly specified assessment instruments, which aim to measure the autonomy of service users, usually determine access to social services. These instruments emphasise functional independence in the performance of activities of daily living. In an effort to broaden the understanding of autonomy into needs assessment practice, the province of Québec (Canada) added social and relational elements into the assessment tool. In the wake of these changes, this article studies the interaction between the use of assessment instruments and the extent to which they alter how older adults define their autonomy as service users. This matters since the conceptualisation of autonomy shapes the formulation of long-term care policy problems, influencing both the demand and supply of services and the types of services that ought to be prioritised by governments. Relying on focus groups, this study shows that the functional autonomy frame dominates problem definitions, while social/relational framings are marginal. This reflects the more authoritative weight of functional autonomy within the assessment tool and contributes to the biomedicalisation of aging.
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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 | 0.080 | 0.277 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".