Info-Santé: A Case Study Of A Disembodied Health Care Service
Bibliographic record
Abstract
AbstractThis study offers an investigation into the history and practice of a teletriage nursing service, Info-Santé. An overview of the Info-Santé service's historical evolution amid cut-backs to the Quebec health care system in the early-to-mid 1990s, with resulting structural changes to health care delivery situates the study within the wider social and political context. The division of labour within the health care system and the place of the Info-Santé nursing service within the health care network are also discussed with a resulting inquiry into an ‘ideal type,' that of ‘Real Nurse.' Two focus groups and in-depth open-ended interviews were conducted with a purposive sample of twenty nurses working in an Info-Santé call center in Sherbrooke, Quebec. In addition, participant observation took place over a period of several months at the same site. Foucault's notion of the clinical gaze is transformed in the absence of a physical ‘patient' in this exploratory case study. Results reveal that these nurses have developed a number of key strategies aimed at ‘hearing' the caller's health problem. In particular, various qualities of the voice as well as the ambient sounds available through the telephone are critical components in the nurses' constructions of the callers and their problems, resulting in the creation of a ‘disembodied' clinical gaze.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.031 | 0.008 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".