Nature's Past Episode 030: Environmental Histories of Montreal
Bibliographic record
Abstract
Last year, the University of Pittsburgh Press published its first book on Canadian urban environmental history titled Metropolitan Natures: Environmental Histories of Montreal. This diverse collection of essays was edited by two leading scholars of Quebec environmental history, Stephane Castonguay and Michele Dagenais. This episode of the podcast explores some of the environmental histories of Montreal. \n \nMontreal is one of the oldest metropolises in North America with a history of Euro-American resettlement and urban development that spans more than four centuries. Prior to European colonization, the island of Montreal was home to the fortified Iroquoian village of Hochelaga. Needless to say, organizing a series of case studies of the environmental history of Montreal is no easy task. Castonguay and Dagenais decided to organize the collection along three broad themes: representations, infrastructures, and hinterlands. The essays in the first section, representations, focus on changing human perceptions of Montreal and its region beginning with the earliest observations of the Island of Montreal and Mount Royal by Jacques Cartier in the 1530s. The following section on “Infrastructures” examines socio-technical systems in the urban environment with particular focus on water systems and roadway infrastructure. In the concluding section of the book on “Hinterlands” the authors explored the changing relationship between city and countryside as Montreal developed as Canada’s leading metropolis. \n \nOn this episode of the podcast, I spoke with two of the authors from this edited collection, Darcy Ingram and Daniel Rueck. \n \nPlease be sure to take a moment to fill out a short listener survey here.
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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 | 0.001 | 0.005 |
| Science and technology studies | 0.015 | 0.005 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 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".