Activism, popular education and knowledge production against temporary employment agency exploitation of im/migrant workers in Montreal
Bibliographic record
Abstract
This thesis examines two intimately related topics. First, it analyzes the practices of temporary employment agencies and employers in using the vulnerabilities of migrant and immigrant workers across different precarious labour sectors in Montreal. Second, it aims to understand the knowledge production, learning and non-formal education linked to action that occur in the course of organizing im/migrant agency workers by the Immigrant Workers Centre (IWC) and the Temporary Agency Workers Association (TAWA). The discussion of agencies is located in a broader context of the global and Canadian neoliberal model which includes attending to racism and racialization, flexible labour and labour deregulation, labour precarity, the defensive position of trade unions, austerity and immigration policies. The study uses longitudinal research and interviews with 42 im/migrant agency workers in precarious jobs, as well as interviews with IWC and TAWA activists and members. It employs an ethnographic and activist approach informed by Global Ethnography and the Extended Case Method. The analysis entailed the description of local experiences of im/migrant agency workers and the ways that agencies manage their vulnerabilities to optimize labour exploitation. It relates IWC and TAWA organizing processes to the growing activity and importance of workers' centres as alternative organizations to traditional trade unionism. The study found that systematic violations of im/migrants' labour rights through agencies also impact their private lives. It argues that the Canadian and Quebec states are complicit in structuring this super-exploitation through their immigration policies and their disengagement from the conditions of im/migrants in the labour market. In response, the IWC and the TAWA have developed an organizing model for agency workers based on five pillars: community organizing, knowledge production, popular education, and leadership development. This includes provision of services infused with education for collective action, arts-based activism, and diverse ways of spreading information and knowledge. Participation in bigger campaigns and partnership with engaged academics has also resulted in important strategies leading to the IWC and the TAWA organizing workers and making visible the problems associated with agencies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".