Railroads, land cessions and Indigenous nations: Evidence from Canada
Bibliographic record
Abstract
Abstract We examine the role that the railroad played in the dispossession and cession of Indigenous lands within the borders of present‐day Canada. Using georeferenced data on the construction of the railroad network and on the timing, content and extent of treaties signed between the Crown and Indigenous nations, we find that the expansion of the railway network does not appear to hasten the signing of treaties or increase the area ceded. However, we find evidence consistent with the Crown engaging in treaty‐signing well in advance of railroad construction to secure the path for the transcontinental railway. We find some weak evidence that US westward expansion, as measured by nearby US population, partly explains the cession of Indigenous lands in what is now Canada. Taken together, our results indicate that the relationship between the railroad and Indigenous land dispossession looked very different in Canada from the United States. In the latter, the process was concurrent; in Canada, land cession occurred well in advance of railway construction. This forward‐looking approach accords with a historical narrative that centres the role of the railway in bringing British Columbia into Confederation and in securing the Prairies from US territorial ambitions.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".