Constructions of frailty in the English language, care practice and the lived experience
Bibliographic record
Abstract
The way frailty is conceptualised and interpreted has profound implications for social responses, care practice and the personal experience of care. This paper begins with an exegesis of the concept of frailty, and then examines the dominant notions of frailty, including how ‘frailty’ operates as a ‘dividing-practice’ through the classification of those eligible for care. The definitions and uses of ‘frailty’ in three discursive locations are explored in: (a) the Oxford English Dictionary , (b) the international research literature, and (c) older women's accounts of their lived experience. Three distinctive discourses are found, and applying a Foucauldian analysis, it is shown that the differences reflect overlaps and tensions between biomedical concepts and lived experiences, as well as negative underlying assumptions and ‘subjugated knowledge’. The concept of frailty represents and orders the context, organisational practices, social representations and lived experiences of care for older people. The evidence suggests that if, as the older women's accounts recommended, socially- and emotionally-located expressions of frailty were recognised in addition to the existing conceptions of risk of the body, frailty might no longer be thought of primarily as a negative experience of rupture and decline. To encourage this change, it is suggested that practice focuses on the prevention of frailty and associated feelings of loss, rather than reinforcing the feelings and experiences which render a person ‘frail’.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.050 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".