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Record W2100360460 · doi:10.30541/v48i2pp.141-153

Demand for Public Health Care in Pakistan

2009· article· en· W2100360460 on OpenAlexaff
Ather H. Akbari, Wimal Rankaduwa, Adiqa Kausar Kiani

Bibliographic record

VenueThe Pakistan Development Review · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Systems and Reforms
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsPer capitaPer capita incomeHealth careGovernment (linguistics)Public healthPublic sectorBusinessPrivate sectorEnvironmental healthSocioeconomicsMedicineEconomic growthEconomicsNursingPopulation

Abstract

fetched live from OpenAlex

A health care demand model is estimated for each province in Pakistan to explain the outpatient visits to government hospitals over the period 1989-2006. The explanatory variables include the number of government hospitals per capita, doctors’ fee per visit at a private clinic, income per capita, the average price of medicine and the number of outpatient visits per capita in the previous period. All variables are significant determinants of the demand for health care in at least one province but their signs, magnitudes and the levels of significance vary. These variations may be attributed to cultural, social and religious factors that vary across provinces. Variations in health care quality offered at public hospitals may also be a factor. These factors and improved accessibility of health care facilities should be the focus of public policy aimed at increasing the usage of public sector health care facilities in Pakistan. JEL classification: I110, I180, O150 Keywords: Health Care, Hospitals, Human Resources, Policy, Public Health

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.192
Threshold uncertainty score0.381

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.072
GPT teacher head0.344
Teacher spread0.272 · 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 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

Citations27
Published2009
Admission routes1
Has abstractyes

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