New York vs. The Canadas: The Saint Lawrence, The Erie Canal, and the Race to Control the American Interior
Bibliographic record
Abstract
This project considers how canal construction was a means for the Canadas and the United States to compete with each other, whether economically or militaristically. I examine canals built from 1815- 1835, the heart of the historiographical “Canal Age,” in the State of New York and the Saint Lawrence Lowlands, specifically the Rideau Canal, the Erie Canal, the Lachine Canal, and the Welland Canal. I argue that geopolitical anxieties and economic competition between the Canadas and the United States engendered canal construction in both nations. Part I discusses the Rideau Canal’s purpose to alleviate British military dependency on the Saint Lawrence. Part II pivots to New York, where I frame the Erie Canal as a tactic by New York business and government interests to deprive Montreal of its geographic monopoly as the sole connection between the Great Lakes and the Atlantic. Part III analyzes the Lachine Canal as Montreal’s economic response to the existential threat the Erie Canal posed to its businesses. Part IV complicates the previous emphasis on militaristic and economic competition to explore moments of international cooperation during the construction of the Welland Canal.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.001 |
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".