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Mobilising modern facts: health technology assessment and the politics of evidence

2006· article· en· W2055543698 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSociology of Health & Illness · 2006
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsnot available
FundersDirektorat Riset and Pengembangan, Universitas IndonesiaEconomic and Social Research CouncilHealth Technology Assessment international
KeywordsNormativeHealth careHealth technologyRigourPublic relationsDisciplinePoliticsMedicineSociologyPsychologyEngineering ethicsPolitical scienceSocial scienceEpistemologyLawEngineering

Abstract

fetched live from OpenAlex

Conventional models of 'evidence' for clinical practice focus on the role of randomised controlled clinical trials and systematic reviews as technologies that promote a specific model of rigour and analytic accountability. The assumption that runs through the disciplinary field of health technology assessment (HTA), for example, is that the quantification of evidence about cost and clinical effectiveness is central to rational policy-making and healthcare provision. But what are the conditions in which such knowledge is mediated into decision-making contexts, and how is it understood and used when it gets there? This paper addresses these questions by examining a series of meetings and seminars attended by senior clinical researchers, social care and health service managers in the UK between 1998-2004, and sessions of the House of Commons Health Committee held in 2001 and 2005. These provide contexts in which questions about the value and utility of evidence produced within the frame of HTA were explored in relation to parallel questions about the design, evaluation and implementation of telemedicine and telecare systems. The paper points to the ways that evidence generated in the normative frame of HTA was increasingly seen as one-dimensional and medicalised knowledge that failed to respond to the contingencies of everyday practice in health and social care settings.

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)0.028
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.368
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0280.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
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 head0.389
GPT teacher head0.495
Teacher spread0.105 · 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