A Comparison of the Development of the Salt Industries in Michigan and Ontario
Bibliographic record
Abstract
“A Comparison of the Development of the Salt Industries in Michigan and Ontario” examines the development of the salt production industry in these two sub-national regions. They derive salt from the same deposit and historically have used very similar methods of mineral extraction, but due to the political differences between the United States and Canada, the trajectories of their growth have been different. The salt industry, which coalesced in the middle of the 19th century, was heavily impacted by the growing forces of capitalism and protectionism (particularly directed by the American interests toward the Canadian manufacturers), and by the impediments of international trade. Salt production in the North American Great Lakes region was also dependent for survival on other industries – first on lumber manufacturing, then on chemical production. However, as underground rock salt mines were created in the 20th century, the economic situations in both countries allowed salt production to become independent for the first time. Although the U.S. industry nearly drove Canadian salt out of business in the late 19th century, in the second half of the 20th century, the mine in Goderich, Ontario, outperformed the mine in Detroit, Michigan, contributing to the greater awareness of the industry in Ontario than in Michigan. The similar but differing paths of these two industries give an informative picture of the ways political boundaries can influence economic development.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".