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Record W2936821653 · doi:10.33423/jabe.v20i2.331

Per Capita GDP, Health Expenditures, and the Income Elasticity of Demand for Health Care in Developing Nations

2018· article· en· W2936821653 on OpenAlexvenueno aff
Adolfo Benavides

Bibliographic record

VenueJournal of Applied Business and Economics · 2018
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPer capitaDeveloping countryPer capita incomeEconomicsHealth careDevelopment economicsDemographic economicsEconomic growthDemographyMedicinePopulationEnvironmental health

Abstract

fetched live from OpenAlex

Using Word Bank’s World Development Indicators data for 130 developing countries and linear and logarithm regression models, this study tests the functional relationship between Per Capita GDP and Per Capita Health Expenditures. Results suggest that health care is neither a luxury nor a necessity for this entire set of countries. However, for nations with an annual per capita GDP less than 2,500 PPP constant 2000 US$, and for countries with GDP per capita over 7,000 PPP constant 2000 US$, medical care is a necessity. Health care is a luxury in developing nations with annual GDP per capita between 2,501 and 7,000 PPP constant 2000 US$.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.745
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.026
GPT teacher head0.369
Teacher spread0.343 · 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 designObservational
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
Published2018
Admission routes1
Has abstractyes

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