MétaCan
Menu
Back to cohort
Record W2018974336 · doi:10.1177/10442073030140021001

Economic Evaluation for Assistive Technology Policy Decisions

2003· article· en· W2018974336 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Disability Policy Studies · 2003
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAssistive technologyHealth technologySet (abstract data type)Field (mathematics)Technology assessmentExposition (narrative)Economic evaluationEmerging technologiesComputer sciencePolicy analysisManagement scienceEngineering managementEngineeringHealth carePolitical scienceHuman–computer interactionMedicineEconomic growthEconomicsArtificial intelligencePublic administration

Abstract

fetched live from OpenAlex

Economic evaluation analysis comprises a set of tools that are used to assess alternative health technologies, including assistive technologies. Health technology assessment is a set of concepts that are used to evaluate technologies and to make policy recommendations. This article presents an exposition of each of these areas: the tools that are used to conduct an economic evaluation, how these tools fit in to the larger policy-related analysis of health technology assessment, and how these tools can be used in the assistive technology field.

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)0.027
metaresearch head score (Gemma)0.132
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
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 score0.304
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0270.132
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
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 head0.521
GPT teacher head0.559
Teacher spread0.038 · 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