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Record W167808383

Examining the Role of Family Physicians in the Decision-Making Processes of Canadian Medical Tourists

2012· article· en· W167808383 on OpenAlexaboutno aff
Rory Johnston

Bibliographic record

VenueSummit (Simon Fraser University) · 2012
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Healthcare and Medical Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsPublic relationsBusinessPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Canadians are increasingly engaging in ‘medical tourism’. Medical tours mark a shift from the gate-keeping model of care provision that underpins diagnostic and surgical care in Canada, wherein family physicians refer patients to specialists, towards care that has a more self-directed role for the patient. This self-direction raises concerns regarding patient safety, chiefly around informed consent and continuity of care. In light of these risks, it is important that we understand how family physicians assist Canadian medical tourists. The analyses indicate that Canadian family physicians are currently only cursorily involved, if at all, in supporting medical tourists in their medical practices. This lack of engagement persists despite physicians’ willingness to be consulted and involved. Improved support for medical tourists by their family doctors is hindered by barriers amongst both stakeholder groups that might be addressed through guidance from medical associations and patient advocacy organizations.

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)0.008
metaresearch head score (Gemma)0.028
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.271

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.004
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.042
GPT teacher head0.327
Teacher spread0.285 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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