Policing Urban Natures: Conservation Officer Work in <scp>O</scp>ttawa and <scp>T</scp>oronto, <scp>C</scp>anada
Bibliographic record
Abstract
Abstract Drawing on the results of interviews and access to information requests, we explore conservation officer work in two urban regions in one Canadian province (Ontario). Specifically, we examine the work of the federal‐level National Capital Commission (NCC) in Ottawa and the provincial‐level Toronto and Region Conservation Authority (TRCA). Applying Jessop, Brenner and Jones's model of socio‐spatial relations, we show how nature plays a different role in NCC and TRCA policing depending on the places their conservation officers work in, the kinds of territorial boundary maintenance in which they engage, the scaling of their activities in various jurisdictions, and the policing networks that they are part of. In assessing the place of nature in conservation officers' work, we contribute to debates about how the boundary between nature and the urban is produced through regulatory practices.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".