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Record W1988209702 · doi:10.1108/13590790510735294

The Canadian response to the Sarbanes‐Oxley Act: managing police resources; a competency‐based approach to staffing

2005· article· en· W1988209702 on OpenAlexaffabout
John Sliter, Carl‐Denis Bouchard, Guy Bellemare

Bibliographic record

VenueJournal of Financial Crime · 2005
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLaw, Economics, and Judicial Systems
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsStaffingBusinessMisconductWhite-collar crimeLaw enforcementHuman resourcesHuman resource managementPublic relationsManagementPolitical scienceLawEconomics

Abstract

fetched live from OpenAlex

Examines how the Royal Canadian Mounted Police (RCMP) successfully implemented a tailor‐made Human Resources (HR) management regime with fresh definitions of competences for the new Integrated Market Enforcement Teams (IMETs). Explains that the intention was to increase competences for investigation of white‐collar crime in the wake of corporate scandals in the USA, and thus to restore investor confidence in Canada’s capital market. Details the IMET pilot project, including selection of personnel from the RCMP for the six IMETs. Concludes that the new HR regime clearly has the ability to change how people are managed in the investigation field.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.782
Threshold uncertainty score0.915

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.221
Teacher spread0.196 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations1
Published2005
Admission routes2
Has abstractyes

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