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Record W4390080653 · doi:10.1177/14613557231218642

Time to drop the mounted: Reimagining a Royal Canadian Gendarmerie

2023· article· en· W4390080653 on OpenAlexaffabout
Chris Madsen

Bibliographic record

VenueInternational Journal of Police Science & Management · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsCanadian Forces College
Fundersnot available
KeywordsScrutinyPublic administrationService (business)Political scienceService memberLawMilitary personnelBusiness

Abstract

fetched live from OpenAlex

As Canada's federal police service celebrates its 150th anniversary, the past and future of the Royal Canadian Mounted Police/Gendarmerie royale du Canada (RCMP/GRC) is coming under intense scrutiny. Dogged by historical legacies and endemic external and internal controversies, this national police service with military characteristics serves the Canadian state loyally and professionally. The anachronistic connection with horses in the English name has long outlived its usefulness and it is time that Canada's federal police service embraced more French, greater inclusivity in the ranks, better accountability and a functional approach to provision of national security policing at higher levels. A new refresh requires rebranding into a truly effective gendarmerie adequately manned, trained and equipped for the task, already anticipated in the French name. Refocusing on federal roles at the national level without the distraction of contract policing would give the RCMP/GRC greater purpose and coherence. The aligned symmetry of a Royal Canadian Gendarmerie/Gendarmerie royale du Canada (RCG/GRC) provides a basis for necessary change to happen and reconciliation to begin.

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)0.006
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.895
Threshold uncertainty score0.765

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0620.016
Scholarly communication0.0120.005
Open science0.0040.007
Research integrity0.0050.012
Insufficient payload (model declined to judge)0.0120.001

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 head0.031
GPT teacher head0.399
Teacher spread0.368 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations1
Published2023
Admission routes2
Has abstractyes

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