The Work of Ownership: Shaping Contestation in Ontario’s Aggregate Extraction Disputes
Bibliographic record
Abstract
This chapter examines the ways in which law 'brackets' human relationships with land to produce and (re)enforce particular forms of land use. It also examines the specific work that legal concepts of ownership perform in disputes about how private land can be used. The chapter discusses the land use planning dispute as one particular space in which disagreements about property occur. Ownership shapes the relationship between private property and planning in order to expose opportunities for the creative rethinking of property relations. Aggregate mineral resources – sand, gravel, rock, and stone – are widely acknowledged to be essential to the built environment as the foundation of infrastructure developments from roads to subways to housing and sewer mains. The centrality of the owner in aggregate extraction decisions is obscured by formal state control of the licensing process and structural opportunities for participation.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.037 | 0.043 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".