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Record W2133541175 · doi:10.20381/ruor-5563

Certainty through Flexibility: Intelligence and Paramilitarization in Canadian Public Order Policing

2012· dissertation· en· W2133541175 on OpenAlexfundvenueaboutno aff
Brad Cartier

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2012
Typedissertation
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsnot available
FundersForeign Affairs and International Trade CanadaTransport CanadaDirektoratet for UtviklingssamarbeidRoyal Bank of Canada
KeywordsAccountabilityOrder (exchange)Political scienceFlexibility (engineering)CertaintyStatement (logic)Public orderField (mathematics)Public administrationPublic relationsSociologyLawManagementBusinessEpistemologyEconomicsMathematics

Abstract

fetched live from OpenAlex

This case study explores public order policing at the Vancouver Olympics and G20 Summit in Toronto. The source material is drawn from media coverage of these events. These cases are analyzed using prior theoretical works in order policing in order to achieve two research goals: to discover which theory best explains police actions and the extent of and reasons explaining the involvement of other government agencies in securing protest events in Canada. Using pattern matching methodology, it was found that no one particular theory is best at explaining events at the two cases, rather components of various theories provided the most useful insight. The components of these theories that need to be amalgamated through analytic induction are: the use of intelligence functions; police flexibility; as well as paramilitarization tactics. Finally, it was found that there was a noticeable presence and integration of other government agencies involved in securing both events.

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)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.932
Threshold uncertainty score0.491

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.005
Science and technology studies0.0190.020
Scholarly communication0.0080.002
Open science0.0020.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.023
GPT teacher head0.256
Teacher spread0.233 · 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 designQualitative
Domainnot available
GenreOther

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

Citations0
Published2012
Admission routes3
Has abstractyes

Explore more

Same venueLibrary and Archives Canada (Government of Canada)Same topicPolicing Practices and PerceptionsFrench-language works237,207