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Record W2122911303 · doi:10.1177/0952076714529141

A politics of priority setting: Ideas, interests and institutions in healthcare resource allocation

2014· article· en· W2122911303 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

VenuePublic Policy and Administration · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsVancouver Coastal Health Research InstituteUniversity of British ColumbiaUniversity of AlbertaVancouver Coastal Health
Fundersnot available
KeywordsAllocative efficiencyPoliticsHealth careResource allocationResource (disambiguation)Set (abstract data type)SociologyPublic administrationEconomicsPolitical scienceLawManagement

Abstract

fetched live from OpenAlex

Across a range of health care systems there is a responsibility placed on meso-level budget holders to set priorities and allocate resources within constrained budgets. The literature suggests that these organizations have typically defaulted to historical and/or political processes for decision making. Whilst the literature on resource allocation in health care attests to the political nature of decision making, this has remained largely under-theorized and therefore priority setters may be unfamiliar with the analytic benefits of applying insights from the broader political sciences. Conversely, policy scientists may know relatively little about existing research on how healthcare organizations make allocative and redistributive decisions. This paper aims to open a dialogue between these solitudes by exploring political effects on health care priority setting, using the interpretive concepts ideas, interests and institutions.

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)0.005
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.738
Threshold uncertainty score0.773

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.006
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 integrity0.0000.000
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 head0.273
GPT teacher head0.449
Teacher spread0.175 · 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