Building and Breaking Nations: The Metis, Capitalism, and States in the North American West, 1870-1935
Bibliographic record
Abstract
This dissertation examines how settler colonization and state formation impacted an Indigenous nation and their identities in the North American West over the late nineteenth and early twentieth centuries. Rather than commonalities, I explore how Métis communities experienced Canada and the United States differently. In the mid-to-late nineteenth century, the Métis witnessed the bison, an essential source of food and trade goods, be nearly eliminated from the northern Great Plains. Canada and the United States had begun to expand national economies westward, leading to mass settlement, commercial agriculture, and continent-wide industrial capitalist and market systems. Although bison hunting had been socially and economically important, I emphasize Métis communities' adaptations to these circumstances. I use census records, estate files, tribal court documents, and other archival material to understand household structures, livelihoods, land tenure, and geographic divisions after the end of the fur trade and during Canadian and American nation-building. In doing so, I highlight Métis socioeconomic cohesion and division over time but show how distinct political and legal contexts shaped family strategies, economic opportunities, and political consciousness. I reveal that Métis communities gradually reworked the concepts of collective identity, governance, and rights depending on their position north or south of the border. I show that this process led to the formation of a distinct Métis national identity in Canada, which did not come together in the United States. By centring the view from below and human agency where possible, this dissertation brings historical processes to the forefront and emphasizes the historical construction of collective identities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".