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Factors influencing rural health care professionals’ access to continuing professional education

2006· article· en· W2091052481 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAustralian Journal of Rural Health · 2006
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsMemorial University of Newfoundland
FundersHealth Canada
KeywordsAttendanceAccreditationRemunerationBest practiceBusinessProfessional developmentContinuing educationNursingHealth careMedical educationPublic relationsMedicinePolitical science

Abstract

fetched live from OpenAlex

OBJECTIVES: The purposes of this study were to explore the perceived barriers and challenges to continuing professional education (CPE) access for Canadian health care professionals and to identify best practices for improving access to CPE. DESIGN: Key informant interviews and Web-based online surveys were conducted. PARTICIPANTS: Key informant interviews were conducted with national CPE accreditation bodies and health professional associations. An online survey was distributed to health professional education programs, as well as provincial professional associations, licensing and professional regulatory bodies. MAIN OUTCOME MEASURES: The perceived barriers and challenges to CPE access for Canadian health care professionals and best practices for improving access to CPE. RESULTS AND CONCLUSIONS: Geographic isolation and poor technological and telecommunications infrastructure were identified as key barriers to CPE delivery and access. Financial factors, such as funding to support travel or cost of attendance, were also identified as major challenges. Tele-education programming was identified as a best practice approach to improve CPE access, as were regional CPE activities and self-directed learning programs. Employer-sponsored initiatives, including staff coverage or locum support, remuneration for time off and paid travel expenses for CPE participation were also identified as best practice approaches.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.449
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.058
GPT teacher head0.486
Teacher spread0.428 · 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