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Record W2098840049

What is medicine? Recruiting high-school students into family medicine.

2006· article· en· W2098840049 on OpenAlexaffabout
Jared Bly

Bibliographic record

VenuePubMed · 2006
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsOutreachFamily medicineMedical schoolMedicineMedical educationNursingPolitical science
DOInot available

Abstract

fetched live from OpenAlex

PROBLEM ADDRESSED: Family medicine is a vital part of health care in Canada. The decline in numbers of new family physicians being trained bodes ill for a sustainable and efficacious health care system. We need to recruit young people more effectively into careers in primary care. Early outreach to high-school students is one approach that holds promise. OBJECTIVE OF PROGRAM: To provide high-school students with exposure to and appreciation for careers in medicine, particularly family medicine. PROGRAM DESCRIPTION: Family medicine residents in the University of Alberta's Rural Alberta North Program initiated an outreach project that was implemented in rural and regional high schools in northern Alberta. The program consisted of visits to high schools by residents who gave interactive presentations introducing medicine as a career. The regional hospital subsequently hosted a career day involving medical and paramedical professionals, such as physicians, pharmacists, nurses, and physical and occupational therapists. CONCLUSION: Physicians' visits to high-school students could be an effective way to increase interest in careers in rural family medicine.

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)0.004
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.027
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0270.004

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 head0.435
Teacher spread0.348 · 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 designNot applicable
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

Citations24
Published2006
Admission routes2
Has abstractyes

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