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Record W2105936887 · doi:10.1002/hec.1344

Estimating differences between male and female physician service provision using panel data

2008· article· en· W2105936887 on OpenAlexafffundabout
Alexandra Constant, Pierre Thomas Léger

Bibliographic record

VenueHealth Economics · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsCenter for Interuniversity Research and Analysis on OrganizationsHEC MontréalHealth Canada
FundersHealth Canada
KeywordsPanel dataContext (archaeology)Service (business)Health careHealth servicesMedicinePopulationDemographyFamily medicineActuarial scienceBusinessEconomicsGeographyMarketingEnvironmental healthEconomic growthEconometricsSociology

Abstract

fetched live from OpenAlex

Using panel data, we estimate the impact of an increasing share of female physicians on the total output of Canadian physicians. A micro-econometric model is developed specifically for the Canadian context and estimated using administrative data on all Canadian physicians paid on a fee-for-service basis from 1989 to 1998. Our results suggest that female physicians systematically provide fewer services than their male counterparts for almost all specialties and provinces studied. Given that females account for an increasing share of the physician population and that female physicians provide, on average, fewer services, potentially important future reductions in total health-care service provision are likely.

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 score0.690
Threshold uncertainty score0.994

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 studies0.0000.000
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 head0.390
GPT teacher head0.349
Teacher spread0.042 · 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

Citations25
Published2008
Admission routes3
Has abstractyes

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