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Record W4242651146 · doi:10.22374/cjgim.v10i3.54

Scholarly Success Among Internal Medicine Residents in Canada

2015· article· en· W4242651146 on OpenAlexaffvenueabout
Katarzyna J. Jerzak, Donald M. Arnold, Shariq Haider

Bibliographic record

VenueCanadian Journal of General Internal Medicine · 2015
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsMcMaster UniversitySunnybrook Health Science Centre
Fundersnot available
KeywordsCurriculumMedical educationMedicinePresentation (obstetrics)Family medicinePsychologyPedagogy

Abstract

fetched live from OpenAlex

Scholar activity is an integral component of postgraduate medical education in Canada. We describe the opportunities in research training among Canadian internal medicine (IM) programs, including program requirements and supportive infrastructure, as well as barriers and enablers of research success. Methods: An email survey was sent to all program directors (PDs) ( n = 14) and core IM residents ( n = 1119) from English-speaking IM Residency Training Programs in Canada to describe research support and productivity. We evaluated factors associated with achieving an abstract presentation at a scientific meeting or publication of a manuscript in a peer-reviewed journal. Results: A total of 10 of 14 PDs (71%) and 308 of 1119 residents (28%) responded to the survey. Of 10 evaluable programs, 6 had a formal research curriculum and 8 had a mechanism of pairing residents with research mentors. A total of 236 (76%) residents completed a research project during core IM training; of those, 171 (55%) published ( n = 84) or presented ( n = 150) their research. A mechanism for linking residents with suitable research mentors, instruction on medical writing, and instruction on data analysis were associated with residents’ achieving publication in a peer-reviewed journal. Conclusion: Requirements for resident research are variable across Canadian IM programs. Instruction on medical writing and statistics, as well as a mechanism to pair residents with suitable research mentors, contribute to resident research success.

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)0.004
metaresearch head score (Gemma)0.053
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.312
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.053
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.123
GPT teacher head0.399
Teacher spread0.276 · 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

Citations1
Published2015
Admission routes3
Has abstractyes

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