MétaCan
Menu
Back to cohort
Record W2904877299 · doi:10.15694/mep.2018.0000286.1

Shifting the paradigm in outreach to under-represented groups

2018· article· en· W2904877299 on OpenAlexafffundabout
Ike Okafor, Lauren Phillips

Bibliographic record

VenueMedEdPublish · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsUniversity of Toronto
FundersUniversity of TorontoMcMaster UniversityMcGill UniversityDalhousie UniversityUniversity of Ottawa
KeywordsMentorshipOutreachDisadvantagedMedical educationDiversity (politics)WorkforceMedical schoolIndigenousPopulationEthnic groupPsychologyPolitical scienceMedicine

Abstract

fetched live from OpenAlex

This article was migrated. The article was marked as recommended. The Community of Support (COS) is a longitudinal and collaborative initiative that enables students who are Indigenous, Black, Filipino, economically disadvantaged, or who self-identify with having a disability to join and receive support at any stage of their medical school journey. The goal of COS is to increase diversity in the fields of research and medicine, as a diverse physician taskforce is essential to meeting the needs of Canada's patient population. Our program supports students at various points in their academic careers, beginning from first year of undergrad to end of PhD and into the workforce. We offer a variety of support systems that aim to address gaps and empower students. Our three-pronged approach provides COS members with support at the levels of i) admissions information, ii) mentorship and experiential opportunities, and iii) application support (including MCAT prep). Over the past 3 years, we have grown to include over 1,100 participants at various stages of their medical school journeys, from first year undergraduate students to university graduates from institution across Canada. As a result, in just three years, we have supported over 80 students with successful admissions to medical school, and alumni from CoS are now represented in 11/15 Canada's medical schools, with a growing number of US schools, such as Yale University, George Washington, Michigan State and Wayne State.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.392
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.045
GPT teacher head0.332
Teacher spread0.287 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2018
Admission routes3
Has abstractyes

Explore more

Same venueMedEdPublishSame topicDiversity and Career in MedicineFrench-language works237,207