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Record W1525241246 · doi:10.22230/jripe.2013v3n1a75

The Experience of GP Surgeons in Western Canada: The Influence of Interprofessional Relationships in Training and Practice

2013· article· en· W1525241246 on OpenAlexvenueaboutno aff
Jude Kornelsen, Stuart Iglesias, Nancy Humber, Nadine R. Caron, Stefan Grzybowski

Bibliographic record

VenueJournal of Research in Interprofessional Practice and Education · 2013
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic shortageContext (archaeology)NursingMedical educationMedicineInterprofessional educationCurriculumHealth carePsychologyPolitical sciencePedagogy

Abstract

fetched live from OpenAlex

Background: Challenges to the sustainability of rural healthcare in Canada demands innovative solutions to human resources shortages in rural communities.One solution is to support generalists with enhanced skills to meet some of the surgical needs of rural residents. Despite favourable outcomes, generalist surgical care is becoming a vanishing option due to the lack of interprofessional support garnered in education and practice.Methods and Findings: Data were gathered through semi-structured interviews with 28 general practitioner surgeons (GPS) face-to-face and 12 GPS over the telephone. Interview participants articulated four themes, including their beliefs about GP surgery, the context of interprofessional relationships between general surgeons and GPS, and qualities of and barriers to interprofessional practice.Conclusions: The importance of establishing positive interprofessional relationships within healthcare in relation to quality of care, outcomes, and system efficiency demands addressing interprofessional challenges at a macro (systems) and micro (personal interaction) level.

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)0.014
metaresearch head score (Gemma)0.026
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.003
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 head0.134
GPT teacher head0.540
Teacher spread0.407 · 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

Citations11
Published2013
Admission routes2
Has abstractyes

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