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Record W3007311452 · doi:10.1093/jcag/gwz047.138

A139 CANADIAN GASTROENTEROLOGY CAREER PATHWAY EXPERIENCES: A GENDER DIVIDE UNDER EXAMINATION

2020· article· en· W3007311452 on OpenAlexaffabout
Noor Jawaid, Monica Boctor, Jordan LoMonaco, Natasha Bollegala

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsSubspecialtyMedicineThematic analysisFamily medicinePsychological interventionDescriptive statisticsDemographyPsychologyQualitative researchNursing

Abstract

fetched live from OpenAlex

Abstract Background The number of Canadian gastroenterologists has been on the rise in the last 20 years but female representation has stayed disproportionately low (30%). Gastroenterology has remained a male dominated subspecialty despite research showing as early as 1990’s that systemic gender-based barriers exist. Aims To determine whether GI career profiles differ between male and female gastroenterologists and understand barriers to career advancement related to gender in order to help shape future interventions to counteract these issues. Methods A 51-question survey was disseminated to gastroenterologists practicing in Canada. Using provincial College of Physicians and Surgeons websites, an electronic survey was sent to GIs with email addresses and a paper copy to those with fax numbers. The Canadian Association of Gastroenterology sent our survey link in their September 2019 membership email. The survey included questions pertaining to personal, professional, financial and practice characteristics of participants. Data was analyzed using SAS statistical program, and descriptive analysis with 95% confidence intervals was used to compare proportions of men and women. Nonparametric tests were used for continuous data. Qualitative thematic analysis was applied for short answer responses. Results Total 98 responses received (14.7% response rate) with 35% female respondents. Majority had adult, urban practices (86%) but males reported significantly more endoscopy time (42% v. 30%) vs. females who spent more time on research (23% v. 10%). Men were more likely to be married and have children than females. Women were more likely to not only have to choose between their marriage and their career, but more chose marriage compared to men specifically taking time off for maternity or childcare needs. Men were more likely to leave childcare predominantly to their spouse whereas women were more likely to share responsibility of childcare with spouse and hired help. Even after adjusting for age, males earned a significantly higher income than females (>$100,000 difference). 40% of men reported a salary over $600,000, compared to only 4% of women. Several gender-based biases were cited by females during their staff GI career: receiving less recognition for their work, challenging relationships with senior colleagues and support staff, inferior promotion opportunity, more difficulty publishing research and having their competency challenged by peers. Conclusions This survey shows that there are still many differences in the Canadian GI career pathway experience based on gender. Female GIs are disproportionately negatively affected in their clinical and academic practices, renumeration and work-life balance. Understanding these disparities is the first step towards remedying gender inequality in GI workplace culture. Funding Agencies None

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.996
Threshold uncertainty score0.455

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0230.004
Scholarly communication0.0060.002
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.000

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 head0.034
GPT teacher head0.235
Teacher spread0.201 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
DomainIncentives
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

Citations2
Published2020
Admission routes2
Has abstractyes

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