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Record W2149077508 · doi:10.1177/1363459307083696

Disciplining death: hypertension management and the production of mortal subjectivities

2007· article· en· W2149077508 on OpenAlexaff
Albert Banerjee

Bibliographic record

VenueHealth An Interdisciplinary Journal for the Social Study of Health Illness and Medicine · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsYork University
Fundersnot available
KeywordsSubjectivityVisionOddsSociologyHealth management systemBiopowerMedicineEpistemologyPolitical scienceAlternative medicinePathologyPhilosophyLawAnthropologyPolitics

Abstract

fetched live from OpenAlex

Medicine powerfully mediates the relationship between life and death. This article argues that in the name of health, modern medicine constitutes a pathological mortal subjectivity, encouraging individuals to experience death as disease, to understand mortality as morbidity, and to approach living instrumentally as a means to longevity. This article uses the example of hypertension management to illustrate how this vision of death is transformed into a form of life. Through the analysis of a number of disciplinary technologies--from technical definitions of health to blood pressure monitoring--it illustrates how individuals are incited to relate to death in an antagonistic, impersonal, and technical fashion. While contemporary forms of capital accumulation in the health field require an intensification of such relations, this article suggests that there much to be gained from exploring visions of health that are not at odds with death.

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)0.005
metaresearch head score (Gemma)0.011
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.025
Scholarly communication0.0080.005
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.079
GPT teacher head0.420
Teacher spread0.341 · 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

Citations8
Published2007
Admission routes1
Has abstractyes

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