Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/57418
Title: Delphi study into 'the impact of amassed corporate biometrics on public and private policing.
Contributor(s): Calladine, Tony
Publication Date: 2023
Open Access: Yes
Handle Link: https://hdl.handle.net/1959.11/57418
Abstract/Context: This study used the Delphi method with a panel of experts from various security and policing agencies. Staged questionnaires were sent online to each expert participant and their responses remained anonymous. During the preliminary round of the study, panel members identified topic areas they considered vital to public safety agencies. Follow-up questionnaires included forced-choice items that drew out the panel members perspectives. The Delphi method proved effective for gathering informed perspectives from experienced operatives working in the field. The study ensured that all relevant aspects were considered by allowing panel members to identify critical areas of focus. The use of forced-choice items assisted in obtaining a clear and concise understanding of the panel’s viewpoints on contemporary issues.
Publication Type: Dataset
Fields of Research (FoR) 2020: 350702 Corporate social responsibility
440204 Crime and social justice
440201 Causes and prevention of crime
440702 Crime policy
440216 Technology, crime and surveillance
Socio-Economic Objective (SEO) 2020: 220199 Communication technologies, systems and services not elsewhere classified
230402 Crime prevention
230404 Law enforcement
Keywords: corporate
biometric data
public police
private police
Location: Globally
HERDC Category Description: X Dataset
Project: A Study into Corporate Social Responsibility and Societal Impact of Biometric Technology on Security within Public and Private Policing.
Dataset Managed By: Tony Calladine
Rights Holder: Tony Calladine
Dataset Stored at: University of New England
Primary Contact Details: Tony Calladine - tonycalladine7@gmail.com
Dataset Custodian Details: Tony Calladine - tonycalladine7@gmail.com
Appears in Collections:Dataset

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open/14969d2b-e785-438d-9574-706b6401f00d.pdfDelphi first round121.95 kBAdobe PDF
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open/dashboard-export-12-34-am-2024-01-18.pdfDelphi Second Round671.22 kBAdobe PDF
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