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Record W1986207791 · doi:10.1097/mlr.0b013e3181eb31d2

A Comparison of Health Care in Canada and the United States

2010· article· en· W1986207791 on OpenAlexaboutno aff
Stephan F. Gohmann

Bibliographic record

VenueMedical Care · 2010
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsnot available
Fundersnot available
KeywordsHealth carePap smearsPopulationPapanicolaou stainPap testMedicinePublic healthDemographyHealth insuranceDemographic economicsFamily medicineEnvironmental healthEconomic growthNursingEconomicsCervical cancer screeningCervical cancerSociology

Abstract

fetched live from OpenAlex

RATIONALE: Compliance with preventive care recommendations differs between countries. Directly comparable data are often not available. The recent release of the Joint Canada/United States Survey of Health makes available data for both Canadians and Americans. OBJECTIVES: The health care systems in the United States and Canada differ quite dramatically. Canadians are covered by a universal health care system while residents of the United States, if they are insured, obtain their insurance from various private or public sources. This paper examines how the use of the Papanicolaou test (Pap smear) by women differs in the United States and Canada. METHODOLOGY: American women are more likely than Canadians to receive a pap smear. A Blinder/Oaxaca type decomposition is used to determine influence of observed population characteristics and unobserved differences between the 2 countries on this gap. RESULTS: The decomposition shows that the gap in Pap smears between Canada and the United States is not influenced by observed demographic differences. Most of the difference is attributable to unobserved heterogeneity or how women are treated in the 2 systems. CONCLUSIONS: Although Canada has universal health coverage, the use of Pap smears is lower than that of all US women and equal to that of uninsured US women. Most of the differences in use of Pap smears is the result of differences in unobserved heterogeneity or the way that the systems treat women which may be a function of differences between the 2 health care systems in marketing, delivering, and reimbursing care.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score0.356

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.040
GPT teacher head0.376
Teacher spread0.336 · 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

Citations8
Published2010
Admission routes1
Has abstractyes

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