Understanding the reproduction of health care: towards geographies in health care work
Bibliographic record
Abstract
There has been only a partial geographical engagement with the production of conventional health care. Whilst medical geography maps aggregate supply and demand features, the geography of health focuses more on consumption and social and cultural contexts. More specifically, apart from a handful of published studies, both of these fields have overlooked how health care is continually reproduced in places by workers. In response to these shortfalls in the literature, we call for attention to geographies in health care work. In support, we describe the geographies that characterize the new health care and, using therapeutics as an example, outline how clinical concepts might provide secure foundations for research. A final discussion outlines the multiple people, places and relationships that could be investigated. Developing geographies in health care work would provide sensitive insights into the complexity, diversity and daily operation of health 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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.004 | 0.026 |
| Scholarly communication | 0.012 | 0.022 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".