How “care values” as discursive practices effect the ethics of a care-setting
Bibliographic record
Abstract
Purpose This paper examines how certain care values permeate, legitimize and authorize hospitalized-older-adults’ care, technologies and practices. The purpose of this paper is to expose how values are not benign but operate discursively establishing “orders of worth” with significant effect on the ethics of the care-setting. Design/methodology/approach The paper draws from a discursive ethnography to see “up close” on a surgical unit how values influence nurse/older-adult-patient care occasions in the domain of older-adults and functional decline. Data are from participant observations, conversations, interviews, chart reviews and reviewed literature. Foucauldian discursive analytics rendered values recognizable and analyzable as discursive practices. Discourse is a social practice of knowledge production constituting and giving meaning to what it represents. Findings Analysis reveals how care values inhere discourses like measurement, efficiency, economics, risk and functional decline (loss of capacity for independent living) pervading care technologies and practices, subjugating older adults’ bodies to techniques, turning older persons into measurable objects of knowledge. These values determine social conditions of worth, objectifying, calculating, normalizing and homogenizing what it means to be old, ill and in hospital. Originality/value Seven older adult patients and attendant nurses were followed for their entire hospitalization. The ethnography renders visible how care values as discursive practices rationalize the social order and operations of everyday care. Analytic outcomes offer insights of how dominant care values enabled care technologies and practices to govern hospitalized-older-adults as a population to be ordered, managed and controlled, eliding possibilities of engaging humanistic patient-centered care.
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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 | 0.032 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.011 | 0.127 |
| Scholarly communication | 0.020 | 0.016 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".