Cross-movement coalitions and political agency: the popular sector and the Pro-Canada/ Action Canada network
Bibliographic record
Abstract
Through a historical account of the Pro-Canada/Action Canada Network (PCN/ACN), this dissertation examines coalition formation among social movements. It argues that the complex process of cross-sectoral coalition formation and thus the \npotential for convergence of social movements can best be understood by combining elements of different analytical frameworks. This dissertation draws on elements of the two dominant paradigms for the study of social movements, resource mobilization theory and new social movement \ntheory. Specifically, it utilizes the formers' attention to the specifics of organization and structure and the latter's focus on the discursive formation of identities. Both are \nthen combined with the uniquely Canadian but theoretically underdeveloped concept of the popular sector and a neo-gramscian perspective on social formation and mobilization that draws on political economy and class-analytical traditions. With its formation in 1988 around opposition to the Canada - U.S. Free Trade Agreement, the PCN/ACN was an early example of a broader trend for trade and investment to become key arenas for social and political contention at the turn of the century. This dissertation challenges the assumptions of most analytical frameworks concerning the limits to coalition formation and argues that the nature of the unifying issue is an important determinant of the potential for the growth and deepening of social alliances. \nAfter reviewing the historical conjuncture in which the PCN/ACN emerged, this dissertation traces the history of key sectors and member organizations - labour, women and ecumenical justice - paying specific attention to their approach to political engagement and the issue of free trade. As a result, it establishes the necessary background to understand both the initial basis for unity and the Network's progression beyond a lowest common denominator alliance around a single issue, to a broader mandate. \nThis dissertation provides empirical evidence on which to judge the potential of social movements to displace other discourses and agencies on the left. Given the contemporary interest in the role of social movements, NGOs and civil society, this dissertation provides some essential signposts for two types of practitioners: academics seeking to understand outcomes and activists hoping to determine them.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.016 | 0.031 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".