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The Hidden Face of Medical Intervention

2019· book-chapter· en· W2943381741 on OpenAlexaff
Samuel Beaudoin

Bibliographic record

VenueAdvances in healthcare information systems and administration book series · 2019
Typebook-chapter
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsArgument (complex analysis)Universal designHealth careEquity (law)Intervention (counseling)Face (sociological concept)RationalityPromotion (chess)Government (linguistics)PoliticsPolitical sciencePublic relationsPopulationEngineering ethicsLaw and economicsManagement scienceMedicineSociologyComputer scienceLawEngineeringSocial scienceNursing

Abstract

fetched live from OpenAlex

In health promotion discourses, access to medical care is presented as a universal remedy. As a result, ethical considerations are often limited to the issue of equitable access. Yet focusing on access to healthcare hides the issue of access to data needed for scientific development. Putting into place a system for saving lives involves population health monitoring and is founded on scientific rationality. This chapter refocuses political attention from medical intervention to what makes it possible. In doing so, the underlying ethical issue shifts from a concern with universal access to healthcare—considered a right from an equity standpoint—to a discussion of the options and consequences of a type of government based on science. The author puts forward the idea that it is not because it is technically and scientifically possible to do something that it should be done. To illustrate this argument, the chapter discusses the example of The Lancet's project on stillbirths (2011-2030) taken up by the WHO.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.991
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.014
GPT teacher head0.317
Teacher spread0.303 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2019
Admission routes1
Has abstractyes

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