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Record W4366830724 · doi:10.1017/cts.2023.300

231 Training Medical Interns and Graduate and Professional Students on Community Engaged Research: Lessons Learned from Implementing a Community Scholars Program

2023· article· en· W4366830724 on OpenAlexfundno aff
Chioma Kas-Osoka, Lexie Lipham, Velma McBride Murry, Consuelo H. Wilkins, Stephania Miller-Hughes, Aima A. Ahonkhai

Bibliographic record

VenueJournal of Clinical and Translational Science · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsnot available
FundersCanada Excellence Research Chairs, Government of Canada
KeywordsOutreachGeneral partnershipMedical educationCommunity engagementProfessional developmentResource (disambiguation)Public relationsPolitical scienceSociologyMedicineComputer science

Abstract

fetched live from OpenAlex

OBJECTIVES/GOALS: 1. Describe the development and implementation of a Community Scholars Program to train graduate and professional students on principles of community engagement and its application to their research. 2. Evaluate lessons learned and overall impact implementing a Community Scholars Program. METHODS/STUDY POPULATION: After identifying a need to train scholars on the principles of community engagement, the Community Engagement Research Core’s (CERC) Community Advisory Council (CAC) developed the Community Scholars Program (CSP) in 2014. The CSP was designed to educate scholars on community engaged research and how it can be applied to their research projects. The program is currently in its ninth cohort with 19 graduate and professional students having participated in the program to date. Prospective scholars identify a community partner and faculty mentor and apply to conduct a community engaged research project over the course of an academic year. The purpose of this project is to describe the development and implementation of a CSP and identify lessons learned throughout the process. RESULTS/ANTICIPATED RESULTS: Five lessons learned have been identified: five major lessons learned from implementing the CSP: (1) establish partnership agreements between the scholars and their community partners and faculty mentors, setting expectations to avoid conflict and increase mutual understanding; (2) expand and implement more creative outreach approaches to cultivate a more diverse pool of applicants; (3) increase networking between current and past scholars to share experiences and serve as a resource for each other; (4) provide formal CE training for scholars to develop a better understanding of the principles of CE and CE research; and (5) document progress of the program through formal feedback and evaluations. DISCUSSION/SIGNIFICANCE: The CSP was constructed to fill a gap in CE research training for graduate and professional scholars. Over the course of the program, the identified lessons learned have created program clarity and increased accountability for scholars, mentors, and community partners alike.

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)0.200
metaresearch head score (Gemma)0.032
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2000.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0120.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.014
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 head0.932
GPT teacher head0.756
Teacher spread0.176 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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