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Record W1976055810 · doi:10.1177/0309132508089826

Understanding the reproduction of health care: towards geographies in health care work

2008· article· en· W1976055810 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProgress in Human Geography · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsMcMaster University
Fundersnot available
KeywordsHealth careHealth geographyWork (physics)Diversity (politics)ReproductionSociologyConsumption (sociology)Public relationsHealth policySocial scienceInternational healthEconomic growthPolitical scienceEcologyAnthropology

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.085
GPT teacher head0.350
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it