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Record W4353015595 · doi:10.1002/jgc4.1698

Barriers in applying to genetic counseling Master's degree programs: Perceptions of prospective applicants when compared with Canadian admissions committee members

2023· article· en· W4353015595 on OpenAlexaffabout
Laura Zahavich, Riyana Babul‐Hirji

Bibliographic record

VenueJournal of Genetic Counseling · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsAccreditationDiversity (politics)Genetic counselingFamily medicineMedicinePublic healthMedical educationProspective cohort studyPsychologyNursingPolitical science

Abstract

fetched live from OpenAlex

The goal of this study was to identify potential barriers in applying to a genetic counseling (GC) Master's degree program to inform strategies for increasing diversity and inclusiveness in the GC student recruitment process. Participants included prospective GC program applicants and admissions committee members from the four Canadian accredited programs. The study was conducted using a quantitative survey-based approach. Twenty-five prospective applicants who previously applied to a GC Master's degree program, 26 who had not applied, and 48 admissions committee members completed the survey. The small number of positions in GC programs was perceived by all groups as highly likely to impact an applicant's ability to gain acceptance to a program as was the limited number of GC training programs. Prospective applicants perceived additional barriers as significantly more likely to impact an individual's ability to apply to/attend a program when compared with admissions committee members including: cost of the application process, the applicant being a visible minority and the applicant having a physical disability. These findings highlight a number of perceived barriers related to applying to a GC Master's degree program. To our knowledge, this is the first study surveying prospective applicants and admissions committee members on barriers faced during the application process. The data from this study can also be used to inform the application process for other health professions.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.599
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.038
GPT teacher head0.285
Teacher spread0.247 · 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 designQualitative
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

Citations6
Published2023
Admission routes2
Has abstractyes

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