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Use of clinical placements as a means of recruiting health care students to underserviced areas in Southeastern Ontario: Part 1 – Student perspectives

2007· article· en· W2054347460 on OpenAlexafffundabout
Michelle MacRae, Kelly Van Diepen, Margo Paterson

Bibliographic record

VenueAustralian Journal of Rural Health · 2007
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsQueen's University
FundersCanadian Medical Association
KeywordsIncentiveAccommodationMedical educationNursingHealth careMedicineIncentive programPsychologyFamily medicinePolitical science

Abstract

fetched live from OpenAlex

OBJECTIVE: This two-part study examines the present gap between financial and educational incentives required and the recruitment strategies used to draw health science students to underserviced areas in Southeastern Ontario. Part 1 explores the impact of offering travel stipends, rent-free accommodation and interprofessional educational opportunities to health science students on their willingness to participate in clinical placements in underserviced areas. DESIGN: Mixed-method two-part study using a self-administered questionnaire. SETTING: Canadian university campus. PARTICIPANTS: Four hundred and sixty-eight senior level medical, nursing, occupational therapy, physical therapy and X-ray technology students from a Canadian university and affiliated professional school. MAIN OUTCOME MEASURES: The influence of currently established incentives on student willingness to complete a clinical placement in designated underserviced communities in Southeastern Ontario. RESULTS: Based on a 75% response rate, the results demonstrate that, in general, students agree that they are more willing to complete a clinical placement in an underserviced community if provided travel stipends (75%), rent-free housing (92%) and interprofessional educational opportunities (65%). Students also identified 15 additional factors influencing willingness. CONCLUSIONS: Students are more willing to complete clinical placements in underserviced communities if provided incentives. The findings of this study support an interprofessional clinical education and recruitment enhancement program in Southeastern Ontario.

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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.266
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.239
GPT teacher head0.563
Teacher spread0.324 · 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.

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

Citations17
Published2007
Admission routes3
Has abstractyes

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