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Record W1970610811 · doi:10.1377/hlthaff.26.4.1159

International Medical Graduate Physicians In The United States: Changes Since 1981

2007· article· en· W1970610811 on OpenAlexaboutno aff
L. Gary Hart, Susan M. Skillman, Meredith A. Fordyce, Matthew Thompson, Amy Hagopian, Thomas R. Konrad

Bibliographic record

VenueHealth Affairs · 2007
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
FundersU.S. Public Health Service
KeywordsQuarter (Canadian coin)PovertyPrimary careFamily medicineMedicineGraduate medical educationMedical educationPolitical scienceGeographyAccreditation

Abstract

fetched live from OpenAlex

Nearly a quarter of all active U.S. physicians are international medical graduates (IMGs)--physicians trained outside the United States and Canada. We describe changes in characteristics of IMGs from 1981 to 2001 and compare them with their U.S. medical graduate (USMG) counterparts. Since 1981, the leading source countries for IMGs have included India, the Philippines, and Mexico. IMGs were more likely to be generalists and to practice in designated underserved areas than USMGs but slightly less likely to practice in isolated small rural areas and persistent-poverty counties. IMGs are an important source of primary care physicians in rural and underserved areas.

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)0.005
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 score0.052
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.087
GPT teacher head0.464
Teacher spread0.377 · 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

Citations101
Published2007
Admission routes1
Has abstractyes

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