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Record W2091113087 · doi:10.1350/ijps.2006.8.3.232

Executive Motivation: From the Front Lines to the Boardroom?

2006· article· en· W2091113087 on OpenAlexaffabout
Steven A. Murphy

Bibliographic record

VenueInternational Journal of Police Science & Management · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsCarleton University
Fundersnot available
KeywordsOvertimeBaby boomersPublic relationsFace (sociological concept)PensionBusinessPerceptionLoomingPsychologyPolitical scienceFinanceDemographic economicsSociologyEconomics

Abstract

fetched live from OpenAlex

This study examines the motivation of rank-and-file police officers to become executives in a large Canadian police force, and the efficacy of the succession management system for the strategic priority of developing the next generation of leaders. The timing of the study is crucial, as police agencies face a looming challenge of managing the retirement of a large number of baby boomers, potentially leaving gaping holes across organisations. The study found that police officers' primary driver for entering the executive ranks is to enhance their own financial security (pension enhancement). Of secondary concern was what police officers could do as executives. Concerns over conflicts with child-rearing and elder care responsibilities, the negative perceptions of executives, workloads, lack of mentoring and the loss of paid overtime were the major negative influences on a decision to become an executive. Important gender differences and cultural issues are discussed to help explain the findings.

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)0.002
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 score0.054
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.002
Scholarly communication0.0040.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.056
GPT teacher head0.325
Teacher spread0.269 · 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

Citations10
Published2006
Admission routes2
Has abstractyes

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