Codification, confusion and crisis: police-government relations when responding to February 2022 protests in Ottawa and Wellington
Bibliographic record
Abstract
This article examines whether the codification of police government relations makes a difference in a crisis. Drawing on detailed official reports about similar protests and occupations of capitals in Ottawa, Canada and Wellington, New Zealand in February 2022, it concludes that codification did not make an appreciable difference to either governmental or police conduct. Governing bodies were reluctant to take responsibility for policing decisions even when they had unfettered statutory powers to do so. At the same time, New Zealand politicians may have pressured the New Zealand Police to engage in an early and unsuccessful attempt to clear the occupation despite broad statutory guarantees of police operational independence, even though the politicians, the police and the inquiry all denied that there was political interference. The article clarifies thinking about police independence by problematising the idea of police operational independence by focusing on policy of operations decisions, specifically whether the police should wear riot gear when policing protests. It also examines the under-studied issue of the relevance of the police chain of command under different conceptions of police independence. It concludes that codification alone will not make police-government relations more transparent or democratic.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.026 | 0.024 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.007 |
| 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".