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Record W2567073085

Sharing the Health: Canada's Market for Prescription Drug Services and its Impact on Self-perceived Health

2016· article· en· W2567073085 on OpenAlexaboutno aff
Connor Paterson

Bibliographic record

VenueLund University Publications Student Papers (Lund University) · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedical prescriptionSocioeconomic statusPrescription drugEnvironmental healthMedicineBusinessHealth careDrugFamily medicineEconomic growthNursingPopulationPharmacologyEconomics
DOInot available

Abstract

fetched live from OpenAlex

Canada is one of the only nations in the world that offers universal health coverage that excludes outpatient prescription drug services. This means that citizens may find out their diagnosis free of charge, but must incur out-of-pocket expenses for prescription drugs dispensed outside of hospitals. This paper examines the prevalence of prescription drug coverage in Canada across various socioeconomic groups, and identifies which specific factors have the strongest bearing on perceived health. The results show that age, education, location and income all play a significant role in determining whether or not individuals are able to obtain coverage, amongst other factors, and that these are proportionally related to how individuals assess their own well-being. This suggests that Canada’s current healthcare system is not as comprehensive as it is made to seem, and that a redesign may be warranted moving forward.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.985
Threshold uncertainty score0.934

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.023
GPT teacher head0.244
Teacher spread0.221 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations0
Published2016
Admission routes1
Has abstractyes

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