Bibliographic record
Abstract
Montreal’s Lachine Canal, once the cradle of Canadian industry, is now riddled with industrial ruins, testaments to its productive past. Since the canal’s closing in the 1970’s, different attempts were made to reinterpret its role within the city. Contaminated sediments pollute the manufactured waterway, now stagnant and derelict. These toxic remains impact the redevelopments and heritage parks of the canal corridor. In the absence of any holistic future vision, these conditions pose a threat to local inhabitants and industrial artifacts. Meanwhile, Parks Canada’s approved heritage status pertaining to certain parts of the canal, further contributes to the segregation of the corridor into sporadic developments and static voids. \n \n \nAntoine Picon refers to these networks of technological remnants as ‘Anxious Landscapes’ – landscapes of artifacts that exist in the realm between technological obsolescence and ruin in the process of returning to nature. These landscapes are charged with industrial ruins and their residues in decay, perceived as waste, make us feel ill at ease with them. Portions of the canal and its industrial artifacts have been identified as having significant heritage value, but what productive possibilities do these heritage artifacts hold beyond their identified status? What possibilities do these imaginative playgrounds possess to reshape the corridor beyond its static blight? \n \n \nIn abandoned industrial icons such as the Canada Malting Plant, resides the potential to address the remediation and reinterpretation of the corridor. The thesis investigates whether interaction with these industrial remnants can permit a tactile connection that allows us to uncover and explore the significance of such landscapes in a larger temporal perspective that considers past, present, and future. It proposes to reveal and express the historical development of the canal, exploring remedial solutions and spaces of community participation, energizing the Lachine Canal and its anxious landscape.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.033 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".