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Asymmetry in Protest Control? Comparing Protest Policing Patterns in Montreal, Toronto, And Vancouver, 1998-2004

2010· article· en· W2339337081 on OpenAlexaboutno aff
Patrick Rafail

Bibliographic record

VenueMobilization An International Quarterly · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)Variation (astronomy)CriminologyLogistic regressionControl (management)SociologyPolitical scienceGeographyEconomicsManagement

Abstract

fetched live from OpenAlex

Scholars have argued that since the 1960s, protest policing in Western democracies has moved toward emphasizing cooperative relationships with challenging groups. This evolution is referred to as the negotiated management model of protest control. Much of the literature that informs this perspective is based on either analyses of a limited subset of demonstrations or from national-level observation. Few studies have examined whether negotiated management practices hold at city levels. This research examines city-level protest policing using 1,152 demonstrations occurring between 1998 and 2004 in Montreal, Toronto, and Vancouver, Canada. Bayesian logistic regression models are estimated using arrests as the response variable. The main findings suggest that only protestor premobilization and the police use of force are uniformly related to arrests; that there is considerable variation across cities; and that the larger pattern of results is not consistent with negotiated management practices.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.227

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0020.002
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.016
GPT teacher head0.326
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations26
Published2010
Admission routes1
Has abstractyes

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