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Record W2415045087 · doi:10.1002/hec.3370

Will the Need‐Based Planning of Health Human Resources Currently Undertaken in Several Countries Lead to Excess Supply and Inefficiency? A Comment on Basu and Pak

2016· letter· en· W2415045087 on OpenAlexaff
Stephen Birch, Gail Tomblin Murphy, Adrian MacKenzie, William Whittaker, Thomas Mason

Bibliographic record

VenueHealth Economics · 2016
Typeletter
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsMcMaster UniversityMcMaster University Medical CentreHamilton Health SciencesDalhousie University
Fundersnot available
KeywordsInefficiencyWorkloadMisrepresentationPublic economicsSocial WelfareHealth careEconomicsBusinessRisk analysis (engineering)Actuarial scienceMicroeconomicsEconomic growth

Abstract

fetched live from OpenAlex

Basu and Pak (2014) argue that need-based workforce planning models would not maximize social welfare, and use of need-based models would result in inefficiency. They propose that planning be based on service utilization to incorporate preferences or other socioeconomic factors. We show that the analysis is based on inappropriate considerations of the nature of healthcare demand, a misrepresentation of need-based approaches and misunderstanding publicly funded healthcare system objectives. We explain how current levels of utilization emerge from workload and income interests of providers that underlie utilization-based models and are incompatible with public goals of maximizing health gains. Copyright © 2016 John Wiley & Sons, Ltd.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.069
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.092
GPT teacher head0.424
Teacher spread0.332 · 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.

Study designNot applicable
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

Citations11
Published2016
Admission routes1
Has abstractyes

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