Explaining infrastructural bifurcation: A comparative history of urban incineration in Montréal and Paris
Bibliographic record
Abstract
This article analyses infrastructural bifurcation in the urban waste management trajectories of two Western metropolises. It identifies the social and political factors that explain why Montréal abandoned waste incineration after a century of use, while this technology has dominated Paris’s waste treatment mix for over 50 years. Inspired by historical comparative urbanism, it zooms in on two specific incinerators, des Carrières in Montréal and Ivry next to Paris, that despite many similarities reveal divergent infrastructural trajectories illustrating larger trends: the decline of waste incineration in North America and its enduring importance in Northern Europe. It argues that deindustrialization and gentrification apply pressure on waste incinerators as relics of industry in dense urban areas. Their closure or survival depends on four intertwined factors: energy systems, maintenance and modernization, urban electoral politics, and land use cultures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".