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Record W3011217342 · doi:10.20529/ijme.2020.027

On being heckled at a National Health Technology Conference: Patient participation and democratic discourse

2020· article· en· W3011217342 on OpenAlexaffabout
Sharon Batt

Bibliographic record

VenueIndian Journal of Medical Ethics · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsDalhousie University
Fundersnot available
KeywordsDemocracyPolitical scienceSociologyPoliticsLaw

Abstract

fetched live from OpenAlex

This article uses my experience of being heckled by patient advocates at a health technology conference in Canada as a springboard for discussing the politics of health technology assessment (HTA). While HTA is widely understood and practised as a scientific endeavour grounded in rigorous quantitative research methods, the socio-political aspects of HTA cannot be separated from the scientific. Integrating the social, political, and ethical dimensions of HTA into the practice of assessment means understanding how a technology will shift power relationships among actors, alter resource flows, and affect how knowledge is produced and circulated. I suggest these factors contributed to the hostile reception I received when I attempted to present a paper about the biased selection of patient advocates involved in Canada's main HTA agency. As India embarks on the challenge of establishing its own agency to support healthcare decision-making, and as patient advocacy groups rise in India with the support of the pharmaceutical industry, I offer this account as a cautionary tale to those shaping India's new agency.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.440
Threshold uncertainty score0.581

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.147
GPT teacher head0.405
Teacher spread0.258 · 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 designTheoretical or conceptual
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

Citations1
Published2020
Admission routes2
Has abstractyes

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