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Rival perspectives in health technology assessment and other economic evaluations for investing in global and national health. Who decides? Who pays?

2018· preprint· en· W2782573323 on OpenAlexaff
Anthony J. Culyer, Kalipso Chalkidou, Yot Teerawattananon, Benjarin Santatiwongchai

Bibliographic record

VenueF1000Research · 2018
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsImpact
FundersThailand Research FundDepartment for International DevelopmentDepartment for International Development, UK GovernmentBill and Melinda Gates Foundation
KeywordsOpen peer reviewPlant biologyHealth technologyMedicinePolitical scienceEconomic growthEconomicsHealth careBiology

Abstract

fetched live from OpenAlex

There seems to be a general agreement amongst practitioners of economic evaluations, including Health Technology Assessment, that the explicit statement of a perspective is a necessary element in designing and reporting research. Moreover, there seems also to be a general presumption that the ideal perspective is "societal". In this paper we endorse the first principle but dissent from the second. A review of recommended perspectives is presented. The societal perspective is frequently not the one recommended. The societal perspective is shown to be less comprehensive than is commonly supposed, is inappropriate in many contexts and, in any case, is in general not a perspective to be determined independently of the context of a decision problem. Moreover, the selection of a perspective, societal or otherwise, is not the prerogative of analysts.

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)0.120
metaresearch head score (Gemma)0.174
Version: metacan-v3-hybrid-931329e0061cValidation 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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.120
Threshold uncertainty score0.636

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1200.174
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0080.009
Science and technology studies0.0040.025
Scholarly communication0.0190.020
Open science0.0030.005
Research integrity0.0150.021
Insufficient payload (model declined to judge)0.0060.001

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 head0.566
GPT teacher head0.600
Teacher spread0.034 · 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 designTheoretical or conceptual
Domainnot available
GenreCommentary

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

Citations23
Published2018
Admission routes1
Has abstractyes

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