A Critical Discourse Analysis of Canada's Throne Speeches Between 1935 and 2015
Bibliographic record
Abstract
The purpose of this thesis was to uncover the tools of manipulation used within political discourses by governments in their attempt to maintain power in society. It specifically asked, How do Canadian federal governments manipulate security, risk, and threat discourses alongside their presentation and understanding of Canadian identity in throne speeches to justify the direction they intend to take the country in with their mandate? This thesis used Critical Discourse Analysis methods to analyze fourteen federal majority government speeches from the throne during the rise and fall of social welfare in Canada. Findings highlight that governments have relatively consistently used the combination of security, risk, and threat discourses between 1935 and 2015. Canadian identity has also been shown to be malleable to government priorities, being connected to notions of collectivism during the rise of social welfare and individualization and productivity during the implementation of neoliberal principles. The introduction of the promise of job creation within the speeches was found to correlate with the introduction of neoliberal principles in Canada. These findings highlight the importance of critical understanding of dominant discourses in society in order to overcome the power they can impose over non-dominant groups.
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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 | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.030 | 0.017 |
| Scholarly communication | 0.012 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".