The 'Feminization' of the Everyday: Examining the Gendered Nature of Worker Resistance within the Transnational Call Center Industry
Bibliographic record
Abstract
This dissertation explores the complex relationships that exist between gender, everyday forms of worker agency and resistance, and the global political economy.I argue that the gendered division of labour within the global political economy has led to the development of gendered opportunity structures of worker resistance.Further, by gendering James C. Scott's conception of a 'spectrum of resistance' (Tripp 1997, p.5; Scott 1993, p.93-94),I assert that the gendered opportunity structures of worker resistance within the Canadian transnational call center can be usefully mapped and interrogated.With women increasingly taking on some of the most precarious jobs in the global economy it has become more difficult for them to pursue more overt and collective forms of action and resistance.Thus, this dissertation examines the role that everyday forms of worker resistance play in challenging unjust and unfair management practices within the highly feminized transnational call center industry, and what significance these actions have for challenging or even disrupting the global political economy.In doing so, the dissertation builds on Scott's foundational work on 'everyday forms of resistance', as well as existing feminist IR and IPE scholarship concerned with the everyday as a central site of analysis.Ultimately this dissertation suggests that in addition to discussing the 'feminization' of certain workforces, it is also necessary to begin discussing the feminization of certain forms of worker resistance as well (Ustubici 2009)-in particular, those forms of resistance which are of a more everyday nature.Additionally, this dissertation presents an explicitly feminist model of 'everyday IPE' (which I refer to as a feminist everyday politics of the global economy, or FEPGE, approach) that builds on Hobson and Seabrooke's (2007) 'EIPE' framework, but which allows for a more nuanced iii understanding of the relationship between gender, everyday actions and resistance, and the international to be brought to light.First, I would like to acknowledge and thank my incredible supervisors, Dr. Fiona Robinson and Dr. Christina Gabriel.I cannot tell you how extremely fortunate I feel to have had you both as a mentors and friends over the last seven years-I am forever indebted to you for your continued support, encouragement, and importantly, your understanding and patience, throughout this entire process.Your feedback and advice on my work has been invaluable, and this dissertation certainly would not be what it is without all the detailed and insightful comments and suggestions you provided.I am so happy that you both generously agreed to be part of my committee-my work has benefitted immeasurably from your input.Also, thank you to my third reader, Dr. Wally Clement.It was an incredible honor and privilege to have you on my dissertation committee.I would also like to
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.032 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".