Reworking Canadian Understanding of Transnational Labour Exploitation
Bibliographic record
Abstract
Within this thesis, I seek to dismantle the dominant narrative pertaining to transnational labour exploitation of garment workers by using the relationship between Canada and Bangladesh as sites of analysis. Overall, the goals of this project are to challenge dominant Canadian understandings of the exploitation of Bangladeshi women workers, and to disrupt the saviour narrative that has launched various ineffective global solidarity projects. I achieve these goals by highlighting the ways in which capitalism, white feminism, and global development programs impact garment workers in Canada and Bangladesh. My project is unique because within it, I bring together the insights of scholars who theorize separately about the Global North and Global South, while also conceptualizing the issue of labour exploitation as a transnational issue, caused by the collective global forces of capitalism, international development, and white feminism. I compare similarities in the struggles faced by garment workers in both Bangladesh and Canada, while also noting how they exhibit agency and challenge exploitation. The research methods that I employ in this project include institutional ethnography, archival research, and personal interviews. I conclude this project by offering more effective approaches to attaining solidarity with garment workers transnationally.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.033 | 0.044 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".