Trudeau Squared: An Analysis of the 1972 and 2021 Canadian Federal Elections
Bibliographic record
Abstract
The Canadian prime ministers Pierre Elliott Trudeau and Justin Trudeau, each serving as leader of the Liberal Party of Canada, governed the country during periods that involved both crisis and social transformation. Related as father and son, the Trudeau prime ministers both experienced strong support upon their initial election to the prime minister’s office and developed a public image among citizens. Pierre Elliott Trudeau and Justin Trudeau were central individuals during the federal elections of 1972 and 2021, being regularly featured in newspaper coverage throughout these re-election campaigns. Comparatively analyzing newspaper coverage and Liberal Party campaign platforms corresponding to these two election periods supports arguments about the agenda of political topics, and details about the framing, tone, and structure within the coverage and platforms. Newspapers shape the process of voters becoming politically informed by reporting on activities of the campaign trail, circulating messages of political parties/candidates, and by shining a spotlight on political issues. Elections communication of political parties and candidates guides agenda setting during campaigns, conjointly influencing and being influenced by mass media outlets. Canadian election campaigns are useful events to employ agenda setting because they generate high levels of newspaper attention and strategic communication by political candidates and parties. Newspaper coverage of the 1972 and 2021 elections features similar political issues such as the economy, employment, and taxes; in particular, an economic slant is heavily present within the coverage. Newspaper coverage from 2021 features a rise in opinionated formats, alongside a subsequent decrease in journalistic objectivity when compared to 1972. While the 1972 Liberal Party platform does not mention Prime Minister Pierre Elliott Trudeau, the 2021 Liberal Party platform is more leader-centric since many of the pledges are framed alongside Prime Minister Justin Trudeau or the opposition party leaders. Newspaper coverage and the Liberal Party platform from 2021 displayed much more adversarial dialogue compared to the 1972 election; direct quotes of Justin Trudeau were also more frequently adversarial compared to Pierre Elliott Trudeau. As political information across the media landscape continues to evolve, newspaper coverage and campaign platforms remain worthwhile communication forms to track agenda setting during elections.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.015 | 0.039 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".