Work in Progress: A Trio-Ethnography on Professional Identity Development of Internationally-Trained Minoritized Women Early-Career Researchers in Canada
Bibliographic record
Abstract
The experiences of internationally trained minoritized academic researchers in engineering and education tend to deviate from the dominant developmental model of the doctoral program and faculty preparation.Our research extended the use of duoethnography methods to trio-ethnography and adapted Carlson and team's conceptual model of professional identity development [1] to investigate how internationally trained minoritized women early career researchers (ECR) build their professional identity construction throughout their doctoral study.Our preliminary findings highlighted three themes namely 1) Perception of Professional Identity, 2) Intersection of Race and Gender, and 3) Learning and Research Communities.The research findings provide approaches for mentoring international minoritized graduate students while improving developmental outcomes for historically racialized groups and other women in similar positions.Our study will contribute to the literature on the professional identity development of international minoritized learners in engineering and education.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.019 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".