Analyzing Online Discourses of Canadian Citizenship: O Canada! True North, Strong, and Free?
Bibliographic record
Abstract
This dissertation reports on findings from a research study that sought to trace how discourses of Canadian citizenship and the resultant social relations that they produce evolved alongside online discussions of Quebec’s proposed Charter of Values. The presentation of The Charter spurred much debate amongst citizens living not only within Quebec, but across Canada, as well. In response, Canadian citizens took to the Internet, among many outlets, to exercise their personal and political agency in order to engage in at times, antagonistic conversations about this controversial socio-political topic. As citizens debated the relative merits of The Charter and voiced their agreement or disagreement with the Quebec government’s proposition, they began to define for themselves what it means to be a citizen. \n \nThis inquiry used corpus-assisted (critical) discourse analysis to examine 34 online discussions concerning The Charter appearing within one online environment (reddit). It aimed at three interrelated objectives: 1) to trace how citizens’ conceptualizations of citizenship and the social relations that they produce evolved alongside online discussions of Quebec’s proposed Charter of Values, 2) to analyze these conceptualizations in order to determine where these articulations converge and/or diverge from existing discourses of citizenship, and 3) to assess the possibility for Canada to constitute a site of both radical and plural democracy. \nFindings from this research reveal that online discussion were framed primarily by discourses of liberal democracy, nationalism, and the current Western security environment, which are deeply in tension with respect to themselves and to one another. Despite these tensions, however, findings reveal that groups who are perceived as occupying majority positions within society often attempt to delegitimize overt counter-discourses that challenge dominant conceptions of Canadian citizenship. Regrettably, this forecloses the possibility of transforming conflicts arising from difference into sites of socio-political flourishing. \n \nThis research highlights the need for citizenship educators to engage with pedagogical strategies that open up spaces for contestation and conflict surrounding issues of privilege, belonging, and cultural difference. Moreover, it forwards potential strategies to converge the on- and offline worlds in favour of citizenship for and within radically democratic and plural societies.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.027 | 0.016 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".