The Canadian Pacific Railway and the Newspapers that Told the Story
Bibliographic record
Abstract
The railways have been an important topic within Canadian history and a large contributor of the founding of Canada. There has been in-depth research in the ways the railroads affected Canada. There was an earlier debate around the idea of why the railway was built exploring possible reasons of national identity, defense from the United States and profiteering from businessmen and politicians. There was another stream of research that takes the Annales school of history approach focusing on the peoples’ lived experiences and drawing many conclusions on how that impacted Canada. There was a post-modernist approach to the effects on Canadian culture from the railways. There is a segment of literature on the opinions of everyday citizens on the railways and those who were in favor of the railways and those opposed to the building of the railways. This research has built a strong narrative of the major events that occurred at the political, business, and working-class citizen level. There has been many different academic approaches and biography’s that tell the story of the individual and the country at large. There was an apparent gap in this research in understanding how the different newspapers covered the Canadian Pacific Railway and the scandal surrounding its building. I argued throughout this thesis that after the founding of Canada in 1867, both the Liberal and Conservative parties of Canada attempted to become the natural governing party of Canada and this fight occurred in the different partisan newspapers and spilled over into debates about the railways.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.059 | 0.021 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.011 | 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".