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Record W4323873774 · doi:10.36834/cmej.36719

Evaluating the impact of a resident research program in general surgery

2017· article· en· W4323873774 on OpenAlexaffvenueabout
Laura Allen, Kelly Vogt, Tina Mele, Michael Ott, K.E. Leslie, Patrick Colquhoun

Bibliographic record

VenueCanadian Medical Education Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsLondon Health Sciences Centre
Fundersnot available
KeywordsProductivityResearch programContext (archaeology)Medical educationMedicineGeography

Abstract

fetched live from OpenAlex

Background: Programs of resident research have been found to improve research productivity. However, evidence of the success of these programs is lacking in a Canadian context. The objective of this study was to evaluate the impact of the introduction of a formal program of resident research at a single Canadian academic centre.Methods: Resident research activities were tracked over a 10-year period (Resident Research Day (RRD) presentations, abstract presentations, published articles). Activities were divided into pre (2002-2007) and post (2007-2012) resident research program implementation time frames. Differences in research productivity were compared between time frames. Surveys of resident attitudes towards research were administered prior to the program’s implementation in 2007, and following introduction of the resident research program in 2009 and 2015.Results: Overall, research productivity (abstracts, publications, and RRD presentations) increased between pre and post resident research program time periods, with a statistically significant increase in mean number of published abstracts. Resident attitudes towards research changed somewhat over time, with fewer residents supporting mandatory research in recent years.Conclusion: Implementation of a resident program of research resulted in a significant increase in research productivity. The setting of clear, modifiable, and achievable goals, as well as providing tools for research success, have contributed to the success of this program.

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)0.025
metaresearch head score (Gemma)0.676
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.920
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0250.676
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.497
GPT teacher head0.663
Teacher spread0.167 · 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

Citations21
Published2017
Admission routes3
Has abstractyes

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