Understanding career persistence of women in engineering in Manitoba: a phenomenological study of former practicing members and graduates never registered
Bibliographic record
Abstract
Women are underrepresented in the Canadian engineering profession at a rate of nearly 10:1 when compared to their male counterparts. This poses a problem for a profession whose goal is to provide innovative and inclusive solutions for all people. In Manitoba, while women are underrepresented in engineering at the same rate as the national average, there is also evidence that some either never enter the profession after graduation or leave at various stages in their career. This qualitative research study examined the experiences of two groups of women in Manitoba, Former Practicing Members and Graduates Never Registered, to understand the factors that both enable and deter their persistence in the engineering profession. Focus group sessions and one-on-one interviews provided an in-depth perspective of factors contributing to women’s career decisions. The findings generally align with the literature-based conceptual framework and indicate that this is a multi-dimensional problem that includes factors such as a need for improved work-life balance, workplace cultural shifts, and confidence building. Implications of these finding include a need to support both new graduates in the licensure process and former members who wish to return to practice.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".