List of Appendices Appendix A- Letter of Invitation I Appendix B- Informed Consent Form
Bibliographic record
Abstract
This research uses the work of Pierre Bourdieu as a starting point for an examination of women's experiences during the pre-tenure stages of their academic career. This thesis is based on six semi-structured interviews with six tenured academic women in the FacuUy of Social Sciences at a medium sized Ontario University. I explore the ranges of experiences that the women report encountering during their pre-tenure years, as well as demonstrate how these experiences are gendered. Through my analysis, I find that women's experiences in academia are shaped by a culture that legitimates their existence in the academic field insofar as they embody the dispositions that reinforce the gendered structure of the academic institution. 1 argue that being measured according to a prototypical male standard creates difficulties for academic women during their pre-tenure years. Acknowledgements Without any embellishment of the truth, this project would not have materialized if it was not for the support, guidance, and contribution provided by special people in my life. These individuals are owed sincere acknowledgement for their involvement in this work. Foremost, I would like show my gratitude by extending a special thank you to my thesis committee members. Dr. Michelle Webber, Dr. Ann Duffy, and Dr. Jane Helleiner. Thank you for having the patience to keep me on track with work, and for breathing life into this study. Michelle, you have served as more than just a supervisor for me, and have given new meaning to the informal responsibilities that academic women so often assume. I would also like to thank my external examiner. Dr. Loma Erwin, for her participation during the final stages of this project. My appreciation must also be extended to the faculty members of both the Social
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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 | 0.013 | 0.108 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.716 | 0.341 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".