Muddy shore to modern port: redimensioning the Montréal waterfront time‐space
Bibliographic record
Abstract
For Montréal in the nineteenth century, as for most port cities, the waterfront served as the primary interface between the city and the markets of the world. This paper examines how and why the primitive waterfront of Montréal as of 1830 was repeatedly adapted and transformed into a modern port district by 1914. Beyond a detailed examination of the set of physical changes on the waterfront, this paper draws theoretical insights from geographical interpretations of the rhythm of capital accumulation to explore the formative and adaptive processes underlying waterfront redevelopment. Global innovations in transport and cargo‐handling technology are recognised as the preconditions for the periodic redimensioning of the port of Montréal, and it is established that these changes were driven by the perennial demands of local investors to accelerate circulation and thus reduce the turnover time of capital. This paper offers a new perspective on waterfront development by conceptualising the entire port as a comprehensive circulatory system and then exploring the redevelopment of various components in relation to others. The findings indicate that massive increases in traffic—the number and size of ships—through the port were correlated with the redimensioning of all of the connected components of the circulatory system; that is, the major arteries such as the St Lawrence River ship channel, as well as the smaller capillaries like finger piers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".