Beyond the Glass Ceiling: How women attain tenure and career progression in stigmatized careers
Bibliographic record
Abstract
The number of employees within the skilled trades in Canada is decreasing, partly due to the retirement of the aging workforce and decreasing incoming employees in the trades. There is also a stigma surrounding the skilled trades, which may cause these careers to be perceived as less attractive for potential incoming employees. Simultaneously, there is a disproportionately low representation of women in the trades. Previous research discussed how stigmatized employees create support buffers to aid in creating a support network to deal with the stigma in their careers. However, there is a gap in the literature regarding how these support networks are formed, what they distinctly consist of, and how this applies to employees that are marginalized in their identities in addition to the stigma that they face due to their careers. This paper examines how individuals working in the trades create support buffers to aid in gaining tenure in their careers, as well as how the support buffers contribute to the individual gaining career progression over time. Using thematic analysis and the long interview method of qualitative data collection, 27 participants including 21 women and six men across various trades and career levels were interviewed to understand their experience with managing stigmatization in their careers. Findings suggest the use of online group platforms was beneficial for women in the trades to create a community to share experiences and resources, possibly due to the anonymity as well as the voluntary nature of the community. Financial incentives and a strong sense of meaningful work also helped employees achieve long-term career progression. This can help various stakeholders to understand how to attract and retain employees in the trades.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".