“A labyrinth of snake pits and traps at every corner” : understanding experiences of Canadian women in building and construction trades through a feminist existential lens
Bibliographic record
Abstract
By 2010, women made up almost half (47%) of the entire Canadian workforce (Ferraro, 2010) and the majority of women work in the service sector with the highest concentration (82%) in the healthcare and social assistance sectors.While the number of women in the workforce has been increasing, there has not been an increase in the number of women in the building trades despite initiatives that have been steadily encouraging women to pursue careers in trades as a viable option to earn a living.The stories of ten female tradespeople were examined using narrative analysis (Riessman, 2008) through a feminist existential lens using the work of de Beauvoir (1976Beauvoir ( , 1989)).Women choosing to pursue a career in trades face much different consequences for their choice than their male counterparts.Through a feminist existential analysis, I argue that the basis of these issues stems from women being viewed as the Other.The major themes that arose from this study were ways in which women are both openly objectified and oppressed at work and how those actions limit their choices, and in turn their existential freedom, creating a space in which they end up working in bad faith.April 19, 2021 To my supervisor, Dr. Albert Mills, I am still not certain how I got here, but I cannot imagine having anyone else guide me through this process.You allowed me to figure it out in my own time and provided insight whenever and wherever it was required.To my committee members, Dr. Meredith Ralston and Dr. Scott MacMillan, your feedback and encouragement were invaluable.I know it took longer than we had all hoped so thank you for sticking it out with me.To my external examiner, Dr. Martin Parker, I thank you for your insight, thought provoking questions
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.066 | 0.066 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".