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Record W2034133043 · doi:10.1080/00050060802438096

Training clinical psychologists for rural and northern practice: Transforming challenge into opportunity

2008· article· en· W2034133043 on OpenAlexaffabout
Karen G. Dyck, Becki L. Cornock, Greg Gibson, AnnaMarie Carlson

Bibliographic record

VenueAustralian Psychologist · 2008
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsTraining (meteorology)Rural areaScarcityMedical educationNorthern territoryMental healthPsychologyNursingMedicineGeographySociologyPsychiatryEthnology

Abstract

fetched live from OpenAlex

The Rural and Northern Program (R&NP) of the University of Manitoba's Department of Clinical Health Psychology (DCHP) is a unique training and service delivery platform that was developed in response to the scarcity of psychological services in rural and northern areas of the province of Manitoba, Canada. Since 1996 rural and northern-based psychologists, in conjunction with the faculty based in Winnipeg (Manitoba's largest city) have offered training to two interns and one postdoctoral resident (resident) yearly. The current article discusses the nature of the program, the regions of Manitoba that the program services, and recruitment and retention data. The authors conclude by offering suggestions for creating sustainable rural/northern psychological practice.

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)0.010
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.008
Scholarly communication0.0070.003
Open science0.0010.010
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.423
GPT teacher head0.586
Teacher spread0.163 · 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 designQualitative
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

Citations10
Published2008
Admission routes2
Has abstractyes

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