Beat the clock! Wait times and the production of ‘quality’ in emergency departments
Bibliographic record
Abstract
Emergency care in large urban hospitals across the country is in the midst of major redesign intended to deliver quality care through improved access, decreased wait times, and maximum efficiency. The central argument in this paper is that the conceptualization of quality including the documentary facts and figures produced to substantiate quality emergency care is socially organized within a powerful ruling discourse that inserts the interests of politics and economics into nurses' work. The Canadian Triage and Acuity Scale figures prominently in the analysis as a high-level organizer of triage work and knowledge production that underpins the way those who administer the system define, measure and evaluate emergency care processes, and then use this information for restructuring. Managerial targets and thinking not only dominate the way emergency work is understood, determined, and controlled but also subsume the actual work of health-care providers in spaces called 'wait times', where it is systematically rendered 'unknowable'. The analysis is supported with evidence from an extensive institutional ethnography that shows what nurses actually do to manage the safe passage of patients through their emergency care process starting with the work of triage nurses.
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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 | 0.011 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.023 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| 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".