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Record W2951536241 · doi:10.1111/maq.12533

Corporate Logic in Clinical Care: The Case of Diabetes Management

2019· article· en· W2951536241 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

VenueMedical Anthropology Quarterly · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsUniversity of Toronto
FundersNational Human Genome Research InstituteNational Science Foundation
KeywordsHealth careQuality (philosophy)BusinessClinical PracticeWork (physics)Public relationsNursingMedicinePolitical scienceEconomicsEconomic growth

Abstract

fetched live from OpenAlex

As large corporations come to dominate U.S. health care, clinical medicine is increasingly market-driven and governed by business principles. We examine ways in which health insurers and health care systems are transforming the goals and means of clinical practice. Based on ethnographic research of diabetes management in a large health care system, we argue that together these organizations redefine clinical care in terms that prioritize financial goals and managerial logics, above the needs of individual patients. We demonstrate how emphasis on quality metrics reduces clinical work to quantifiable outcomes, redefining diabetes management to be the pursuit of narrowly defined goal numbers, despite often serious health consequences of treatment. As corporate employees, clinicians are compelled to pursue goal numbers by the heavy emphasis payers and health systems place on quality metrics, and accessing the required medications becomes the central focus of clinical practice.

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)0.015
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.230
GPT teacher head0.452
Teacher spread0.222 · 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