Udvidet returret til d. 31. januar 2025

Bøger af Andromachi Tseloni

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  • af Nick Tilley, Andromachi Tseloni & Rebecca Thompson
    1.592,95 kr.

    Domestic burglary has fallen significantly over the past 20 years in many countries, but still remains a high volume crime. On top of substantial financial loss and property damage, burglary also leads to high levels of anxiety and fear of crime. The research presented in this book represents the first systematic study of what actually works in security interventions against burglary, with cross-sectional data on different regions and socio-economic population groups. This work provides an overview of the scope of the problem and what can be done about it, drawing on extensive research evidence from projects funded by the Economic and Social Research Council (ESRC) Secondary Data Analysis Initiative (SDAI), and other sources. It reports detailed findings about which interventions are most effective for different population groups and how these measures can be implemented. It includes burglary prevention advice for homeowners, law enforcement and other public agencies, and makes recommendations for future research.In addition to being relevant to concerned citizens, police, policy-makers and crime prevention practitioners, this book will also be of interest to researchers in criminology and criminal justice, particularly those working on security and crime prevention, as well as urban planning and public policy.

  • - New Directions in Research
    af Andromachi Tseloni
    780,95 kr.

    Drawing on new studies from major European countries and Australia, this exciting collection extends the ongoing debate on falling crime rates from the perspective of criminal opportunity or routine activity theory. It analyses the effect of post WW2 crime booms which triggered a universal improvement in security across the Western world.

  • af Ken Pease & Andromachi Tseloni
    554,95 kr.

    The authors of this work have found more accurate ways to predict and prevent victimization using a statistical modeling, based around crime concentration and sub-group profiling with regard to crime vulnerability levels, to predict areas and individuals vulnerable to crime.

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