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Discriminant analysis predicted undisciplined policemen

In the wider spectrum of Taiwanese public service spheres, the herculean services and dedication of its committed Police personnel have long been recognized, respected, and admired. However, regrettably, question marks concerning their conduct, discipline, and abuse of power have surfaced on intermi...

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Autores principales: Liu, Kuang-Tai, Yu, Ryi-Kui, Ma, Hsin-Yun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10399267/
https://www.ncbi.nlm.nih.gov/pubmed/34783615
http://dx.doi.org/10.1177/00368504211055638
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author Liu, Kuang-Tai
Yu, Ryi-Kui
Ma, Hsin-Yun
author_facet Liu, Kuang-Tai
Yu, Ryi-Kui
Ma, Hsin-Yun
author_sort Liu, Kuang-Tai
collection PubMed
description In the wider spectrum of Taiwanese public service spheres, the herculean services and dedication of its committed Police personnel have long been recognized, respected, and admired. However, regrettably, question marks concerning their conduct, discipline, and abuse of power have surfaced on intermittent occasions. A classic example that lingers in the public memory is the bribing of Taiwanese video game companies to some unscrupulous elements of the police department, in the closing decades of the 20th century that triggered public outrage and called for scrutiny concerning serious lapses in the discipline and conduct of Police personnel. This research paper endeavors to understand, analyze and address some of those issues based on empirical data on the police personnel of certain specific work zones/areas taking into account holistically both the sentenced police officers vis-à-vis the law-abiding police officers. This module looks into and sieves through available data for seven critical variables, including their degree of variation through the Identification and Analysis Method to develop a Predictive Model on Police Ethics and the important factors that affect Police Ethics. Concretely based on the integrated research, it is proposed that this Predictive Model has good applicability as well as accurate predictive ability in addressing the core issues that affect Police Ethics. It is hoped that through this Early Warning Predictive Model—all the stakeholders that are Policy and Decision-makers, Regulatory Police Agencies but more importantly the Police personnel themselves would effectively address the criticality of the issues that affect the Police Ethics so as to undertake competent and effective measures to erase/lessen the menace and provide an early rehabilitative care/assistance to build a strong, constructive and visionary Taiwanese Police Force to meet the challenges of 21st century and beyond.
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spelling pubmed-103992672023-08-09 Discriminant analysis predicted undisciplined policemen Liu, Kuang-Tai Yu, Ryi-Kui Ma, Hsin-Yun Sci Prog Conference Collection IMETI 2020 In the wider spectrum of Taiwanese public service spheres, the herculean services and dedication of its committed Police personnel have long been recognized, respected, and admired. However, regrettably, question marks concerning their conduct, discipline, and abuse of power have surfaced on intermittent occasions. A classic example that lingers in the public memory is the bribing of Taiwanese video game companies to some unscrupulous elements of the police department, in the closing decades of the 20th century that triggered public outrage and called for scrutiny concerning serious lapses in the discipline and conduct of Police personnel. This research paper endeavors to understand, analyze and address some of those issues based on empirical data on the police personnel of certain specific work zones/areas taking into account holistically both the sentenced police officers vis-à-vis the law-abiding police officers. This module looks into and sieves through available data for seven critical variables, including their degree of variation through the Identification and Analysis Method to develop a Predictive Model on Police Ethics and the important factors that affect Police Ethics. Concretely based on the integrated research, it is proposed that this Predictive Model has good applicability as well as accurate predictive ability in addressing the core issues that affect Police Ethics. It is hoped that through this Early Warning Predictive Model—all the stakeholders that are Policy and Decision-makers, Regulatory Police Agencies but more importantly the Police personnel themselves would effectively address the criticality of the issues that affect the Police Ethics so as to undertake competent and effective measures to erase/lessen the menace and provide an early rehabilitative care/assistance to build a strong, constructive and visionary Taiwanese Police Force to meet the challenges of 21st century and beyond. SAGE Publications 2021-11-16 /pmc/articles/PMC10399267/ /pubmed/34783615 http://dx.doi.org/10.1177/00368504211055638 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Conference Collection IMETI 2020
Liu, Kuang-Tai
Yu, Ryi-Kui
Ma, Hsin-Yun
Discriminant analysis predicted undisciplined policemen
title Discriminant analysis predicted undisciplined policemen
title_full Discriminant analysis predicted undisciplined policemen
title_fullStr Discriminant analysis predicted undisciplined policemen
title_full_unstemmed Discriminant analysis predicted undisciplined policemen
title_short Discriminant analysis predicted undisciplined policemen
title_sort discriminant analysis predicted undisciplined policemen
topic Conference Collection IMETI 2020
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10399267/
https://www.ncbi.nlm.nih.gov/pubmed/34783615
http://dx.doi.org/10.1177/00368504211055638
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