Winning back more than words? Power, discourse and quarrying on the Niagara Escarpment
Bibliographic record
Abstract
This paper explores the controversy and public hearing on the proposed extension of the largest limestone quarry in Canada, operated by Dufferin Aggregates at Milton, Ontario. The quarry constitutes an important source of construction material for the nearby Greater Toronto Area. However, the quarry is protected by the provincial Niagara Escarpment Planning and Development Act and located inside the UNESCO‐designated Niagara Escarpment Biosphere Reserve. The proposal has therefore attracted considerable opposition from the public institution charged with its protection, the Niagara Escarpment Commission, as well as environmental groups and local residents. To make sense of the tensions, conflicts and outcome of the Dufferin case, we consult and apply several critical literatures. We see the conflict as part of a transformation of the countryside from a space of production to a space of consumption, where there is a shift in emphasis from resource extractive to scenic and ecological landscape values, and the displacement of productive classes, farmers and workers, in favour of a service class of professionals and retirees. Within this transformation, we identify a ‘power geometry’ of actor networks of different coalition groups that form allegiances and engage in struggles at different geographic scales. These actor networks operate within the set frames of a dominant development discourse and a popular environmentalist discourse that both include and exclude other ways of seeing and managing the escarpment.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.039 | 0.055 |
| Scholarly communication | 0.016 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| 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".