Mediating transgressions : the global justice movement and Canadian news media
Bibliographic record
Abstract
The focus of this thesis is the problematic, paradoxical relationship between the mass media and social movements. It is about how news media practices naturalize the hegemonic status quo, containing dissent and incorporating it into this ideological space. In Chapter 1, I lay out the theoretical framework upon which my analysis is based, examining the notion of the news media as a discursive battleground through the lenses of media studies, political economy, newsmaking theory, and Foucauldian theories of discourse and power. Chapter 2 begins with an exploration of the global justice movement--its origins, its analysis--as this context is imperative in conducting a critical discourse analysis. Drawing on print news media coverage of the movement, I then go on to explore how this movement is represented within mainstream Canadian newspapers, asking specifically how the 'war on terror' has impacted this movement's access to this discursive battleground. Chapter 3 addresses one of the most contentious questions within the movement--how does "symbolic violence" (acts against property not people) get covered within news media, and, what are the effects of this?--analyzing whether the price of entry to this sphere is the re-presentation of events in such a way that smashed windows and graffiti are the only images portrayed, or, whether activists benefit from the space created by symbolic violence. To conclude, I discuss possible interventions for both activists and researchers that, in light of this project, maybe useful in waging discursive resistance.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.038 | 0.030 |
| Scholarly communication | 0.024 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".