The Experts below are selected from a list of 276 Experts worldwide ranked by ideXlab platform
Adam Crawford - One of the best experts on this subject based on the ideXlab platform.
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criminalizing sociability through anti social Behaviour legislation dispersal powers young people and the police
Youth Justice, 2009Co-Authors: Adam CrawfordAbstract:This article explores the impact of dispersal powers introduced as part of the British government's drive to tackle Anti-Social Behaviour. It focuses especially on the experiences and views of young people affected by dispersal orders. It highlights the importance of experiences of respect and procedural justice for the manner in which they respond to directions to disperse. It considers the ways in which dispersal powers can increase police—youth antagonism; bring young people to police attention on the basis of the company they keep; render young people more vulnerable; and reinforce a perception of young people as a riskto others rather than asat riskthemselves. It reflects on broader conceptions of youth and public space apparent within the Anti-Social Behaviour agenda.
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dispersal powers and the symbolic role of anti social Behaviour legislation
Modern Law Review, 2008Co-Authors: Adam CrawfordAbstract:This article considers the development and use of dispersal powers, introduced by the Anti-Social Behaviour Act 2003, and situates these within the context of wider legislation and policy initiatives. It explores the ways in which the powers have been interpreted by the courts and implemented by police and local authorities. The article critically analyses the manner in which the powers: introduce ‘public perceptions’ as a justification for police encroachments on civil liberties; conform to a hybrid-type prohibition; constitute a form of preventive exclusion that seeks to govern future Behaviour; are part of a wider trend towards discretionary and summary justice; and potentially criminalise young people on the basis of the anxieties that groups congregating in public places may generate amongst others. It is argued that the significance of dispersal orders derives as much from the symbolic messages and communicative properties they express, as from their instrumental capacity to regulate Behaviour.
Vincent Egan - One of the best experts on this subject based on the ideXlab platform.
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personality the dark triad and violence
Personality and Individual Differences, 2014Co-Authors: Andrea Pailing, Julian Boon, Vincent EganAbstract:Abstract Aggression involves using force to dominate a situation, whereas violence uses force to do intentional harm. Previous research suggests the Dark Triad underlies much Anti-Social Behaviour, and is associated with aggression. We extend this work to examine whether Dark Triad constructs predict self-reported violence. The Dark Triad, measured using the SD3, was examined in relation to normal personality traits as indexed by the HEXACO, which comprises a general Big Five structure with the addition of an Honest–Humility dimension. We also measured impulsivity using the I-7. A sample of 159 adults completed the measures. Principal Components Analysis revealed Machiavellianism, psychopathy and violence loaded on the same factor, which also had negative loadings for HEXACO domains of Honesty–Humility and Agreeableness. Narcissism loaded on a separate factor which was also defined by Extraversion. Hierarchical regression analyses found Agreeableness a more powerful predictor of violence than psychopathy or Machiavellianism, both of which showed a trend to this association; narcissism had no effect. Agreeableness emerged as the strongest negative predictor of violence, and exclusively explained the majority of variance in violence scores. Findings are discussed regarding the centrality of low agreeableness as a driving force behind the Dark Triad and the constructs it predicts.
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the dark triad and normal personality traits
Personality and Individual Differences, 2006Co-Authors: Sharon Jakobwitz, Vincent EganAbstract:Abstract Machiavellianism, Narcissism and Psychopathy are often referred to as the ‘dark triad’ of personality. We examined the degree to which these constructs could be identified in 82 persons recruited from the general population, predicting that the dark triad would emerge as a single dimension denoting the cardinal interpersonal elements of primary psychopathy. We expected the primary psychopathy dimension to correlate negatively with Agreeableness (A) and Conscientiousness (C), whereas secondary psychopathy would be associated with Neuroticism (N). The negative correlation was found between primary psychopathy and A, but not with C. While the predicted correlation between secondary psychopathy and N was found, N was also positively associated with primary psychopathy and Machiavellianism. Factor analysis revealed that all measures of the dark triad loaded positively on the same factor, upon which A loaded negatively. Secondary psychopathy loaded positively on a second factor, together with N and (negatively) with C. These findings reiterate the distinguishing properties of secondary psychopathy, impulsivity and Anti-Social Behaviour relative to primary psychopathy. Thus, even in the general population, the dark dimension of personality can be described in terms of low A, whereas much of the Anti-Social Behaviour in normal persons appears underpinned by high N and low C.
Moradi, Mohammad Mehdi - One of the best experts on this subject based on the ideXlab platform.
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Spatial and spatio-temporal point patterns on linear networks
2021Co-Authors: Moradi, Mohammad MehdiAbstract:The last decade witnessed an extraordinary increase in interest in the analysis of network related data and trajectories. This pervasive interest is partly caused by a strongly expanded availability of such datasets. In the spatial statistics field, there are numerous real examples such as the locations of traffic accidents and geo-coded locations of crimes in the streets of cities that need to restrict the support of the underlying process over such linear networks to set and define a more realistic scenario. Examples of trajectories are the path taken by moving objects such as taxis, human beings, animals, etc. Intensity estimation on a network of lines, such as a road network, seems to be a surprisingly complicated task. Several techniques published in the literature, in geography and computer science, have turned out to be erroneous. We propose several adaptive and non-adaptive intensity estimators, based on kernel smoothing and Voronoi tessellation. Theoretical properties such as bias, variance, asymptotics, bandwidth selection, variance estimation, relative risk estimation, and adaptive smoothing are discussed. Moreover, their statistical performance is studied through simulation studies and is compared with existing methods. Adding the temporal component, we also consider spatio-temporal point patterns with spatial locations restricted to a linear network. We present a nonparametric kernel-based intensity estimator and develop second-order characteristics of spatio-temporal point processes on linear networks such as K-function and pair correlation function to analyse the type of interaction between points. In terms of trajectories, we introduce the R package trajectories that contains different classes and methods to handle, summarise and analyse trajectory data. Simulation and model fitting, intensity estimation, distance analysis, movement smoothing, Chi maps and second-order summary statistics are discussed. Moreover, we analyse different real datasets such as a crime data from Chicago (US), Anti-Social Behaviour in Castell´on (Spain), traffic accidents in Medell´ın (Colombia), traffic accidents in Western Australia, motor vehicle traffic accidents in an area of Houston (US), locations of pine saplings in a Finnish forest, traffic accidents in Eastbourne (UK) and one week taxi movements in Beijing (China)
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Spatial and spatio-temporal point patterns on linear networks
2021Co-Authors: Moradi, Mohammad MehdiAbstract:A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management, specialization in Geographic Information SystemsThe last decade witnessed an extraordinary increase in interest in the analysis of network related data and trajectories. This pervasive interest is partly caused by a strongly expanded availability of such datasets. In the spatial statistics field, there are numerous real examples such as the locations of traffic accidents and geo-coded locations of crimes in the streets of cities that need to restrict the support of the underlying process over such linear networks to set and define a more realistic scenario. Examples of trajectories are the path taken by moving objects such as taxis, human beings, animals, etc. Intensity estimation on a network of lines, such as a road network, seems to be a surprisingly complicated task. Several techniques published in the literature, in geography and computer science, have turned out to be erroneous. We propose several adaptive and non-adaptive intensity estimators, based on kernel smoothing and Voronoi tessellation. Theoretical properties such as bias, variance, asymptotics, bandwidth selection, variance estimation, relative risk estimation, and adaptive smoothing are discussed. Moreover, their statistical performance is studied through simulation studies and is compared with existing methods. Adding the temporal component, we also consider spatio-temporal point patterns with spatial locations restricted to a linear network. We present a nonparametric kernel-based intensity estimator and develop second-order characteristics of spatio-temporal point processes on linear networks such as K-function and pair correlation function to analyse the type of interaction between points. In terms of trajectories, we introduce the R package trajectories that contains different classes and methods to handle, summarise and analyse trajectory data. Simulation and model fitting, intensity estimation, distance analysis, movement smoothing, Chi maps and second-order summary statistics are discussed. Moreover, we analyse different real datasets such as a crime data from Chicago (US), Anti-Social Behaviour in Castell´on (Spain), traffic accidents in Medell´ın (Colombia), traffic accidents in Western Australia, motor vehicle traffic accidents in an area of Houston (US), locations of pine saplings in a Finnish forest, traffic accidents in Eastbourne (UK) and one week taxi movements in Beijing (China)
Carol Tannahill - One of the best experts on this subject based on the ideXlab platform.
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is concern about young people s anti social Behaviour associated with poor health cross sectional evidence from residents of deprived urban neighbourhoods
BMC Public Health, 2012Co-Authors: Matt Egan, Lyndal Bond, Ade Kearns, Carol TannahillAbstract:Background Young people in disadvantaged neighbourhoods are often the focus of concerns about Anti-Social Behaviour (ASB). There is inconsistent evidence to support the hypothesis that perceptions of ASB (PASB) are associated with poor health. We ask whether perceptions of young people's ASB are associated with poor health; and whether health, demographic and (psycho)social characteristics can help explain why PASB varies within disadvantaged neighbourhoods (Glasgow, UK).
David Prior - One of the best experts on this subject based on the ideXlab platform.
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the problem of anti social Behaviour and the policy knowledge base analysing the power knowledge relationship
Critical Social Policy, 2009Co-Authors: David PriorAbstract:The high priority given to tackling Anti-Social Behaviour in current government policy might generate an expectation that knowledge of the nature and extent of the problem would provide an empirica...