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Record W2125270132 · doi:10.1525/maq.2004.18.4.490

In Visible Bodies: Minority Women, Nurses, Time, and the New Economy of Care

2004· article· en· W2125270132 on OpenAlexaffabout
Denise L. Spitzer

Bibliographic record

VenueMedical Anthropology Quarterly · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicRacial and Ethnic Identity Research
Canadian institutionsUniversity of Alberta
FundersPan African Materials Institute
KeywordsRestructuringFeelingBureaucracyNursingHealth careContext (archaeology)RacismMedicinePolitical sciencePsychologyEconomic growthSociologyGender studiesSocial psychologyPoliticsEconomicsHistory

Abstract

fetched live from OpenAlex

Health care reform in Canadian hospitals has resulted in increased workloads and bureaucratization of patient care contributing to the development of a new economy of care. Interviews with nurses and visible (non-white) minority women who have given birth in institutions undergoing health care reform revealed that nurses felt compelled to avoid interactions with patients deemed too costly in terms of time. Overwhelmingly, these patients were members of culturally marginalized populations whose bodies were read by nurses as potentially problematic and time consuming. As their calls for assistance go unanswered, visible minority women complained of feeling invisible. Taken in context of historical and contemporary interethnic relations, these women regarded such avoidance patterns as evidence of racism. Obstetrical nurses, too, understood that the new economy of care wrought by health care restructuring has altered nursing practice and patient care to the detriment of minority women.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.133
Threshold uncertainty score0.265

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.028
Scholarly communication0.0060.004
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.345
Teacher spread0.336 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations58
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueMedical Anthropology QuarterlySame topicRacial and Ethnic Identity ResearchFrench-language works237,207