Bibliographic record
Abstract
Professional urban fire services across the United States and Canada are now engaged in care work, as a significant aspect of their work as emergency medical first responders. Given that the historically resilient world-wide unequal gendered division of labour continues to assign care to women, and to subaltern women in particular, the engagement of this primarily white, male labour force bears examination. In Canada, the late 1990s saw fire responses to ‘medical’ emergencies increase dramatically to become the dominant call category for fire services, as part of a tiered emergency response. Further, these responses are seldom to heart attack, stroke or catastrophic events for which firefighters are trained, but instead are responses to more predictable and recurring issues imperiling the health and well-being of people with chronic illnesses, disability or frailty. Using data collected from research in four Canadian cities, this article explains how fire services have been pulled into emergency care concurrent with health care and social services re-structuring and what this move tells us about re-structuring in terms of the fragility of the care economy and masculinized public sector work.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.105 | 0.032 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.006 | 0.011 |
| 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".