Find the secret to improve the quality of life by reading this group based modeling of development. This is a kind of book that you need now. Besides, it can be your favorite book to read after having this book. Do you ask why? Well, this is a book that has different characteristic with others. You may not need to know who the author is, how well-known the work is. As wise word, never judge the words from who speaks, but make the words as your good value to your life.

Group-Based Modeling of Development

Predicting when and where crimes are likely to occur is crucial for prioritizing police resources. Prior victimization is an excellent predictor of risk. Repeat victimization, when it occurs, tends to occur swiftly after an initial incident. The predictive power of prior victimization is greater than that of other analysed variables (see Budd 1999). Self-evidently, prior victimization yields no prediction about properties as yet unvictimized. This article, using data about the crime of domestic burglary, contends that research should seek to realize the predictive potential to be gained from both pre-and post-victimization factors. One of the advantages of crime reduction through the prevention of repeats is that it offers a constant (and, it is hoped, declining) rate of events that trigger preventive action, and hence a natural pace for preventive work. In that spirit, postvictimization prevention should, as well as targeting the victimized home, also protect other properties that are similar with respect to the dimensions used by burglars in target selection. The central purpose of the research here reported is to identify the ways in which it is prudent to allocate crime reduction resources in the wake of an offence and across time and location relative to the burgled home. We analysed police-recorded crime burglary data for the county of Merseyside. Using statistical techniques developed to study the transmission of disease, we first confirmed that burglaries do cluster in space and time. The operational payoff of this result is that a residential burglary flags the elevated risk of further residential burglaries in the near future (1-2 months) and in close proximity (up to 300-400 metres) to the victimized home. Put simply, the burglary event should trigger preventive action that is not restricted to the burgled home. The data enable prospective burglary hot-spotting.

The Burglary as Clue to the Future: The Beginnings of Prospective Hot-Spotting

Online mapping technologies such as Google Maps and Street View have become increasingly accessible. These technologies have many convenient uses in everyday life, but law enforcement agencies have expressed concern that they could be exploited by offenders and might alter existing offending patterns and habits. For environmental criminologists, they have the potential to open up new approaches to conducting research. This paper draws on the results of earlier studies in related fields and a handful of criminological studies to discuss how these online mapping applications can trigger new research questions, and how they could be considered a valuable methodological addition to criminological research.

https://biblio.ugent.be/publication/4344882/file/5763027.pdf

Should criminologists be feeling lucky!? Applying Google Maps and Google Street View in criminological research

How COVID-19 reshaped quality of life in cities: A synthesis and implications for urban planning.

බළන්ගොඩ ප්රදේශය ආශ්රිත ශාන්තිකර්ම පිළිබඳ තුලනාත්මක අධ්යයනයක් (Unpublished doctoral dissertation)

Governments around the world have enforced strict guidelines on social interaction and mobility to control the spread of the COVID-19 virus. Evidence has begun to emerge which suggests that such dramatic changes in people’s routine activities have yielded similarly dramatic changes in criminal behavior. This study represents the first ‘look back’ on six months of the nationwide lockdown in England and Wales. Using open police-recorded crime trends, we provide a comparison between expected and observed crime rates for fourteen different offence categories between March and August, 2020. We find that most crime types experienced sharp, short-term declines during the first full month of lockdown. This was followed by a gradual resurgence as restrictions were relaxed. Major exceptions include anti-social behavior and drug crimes. Findings shed light on the opportunity structures for crime and the nuances of using police records to study crime during the pandemic.

/pdf/six-months-in-pandemic-crime-trends-in-england-and-wales-4wzmkt19gs.pdf

Six months in: pandemic crime trends in England and Wales

Residential burglary target selection: An analysis at the property-level using Google Street View

Police-recorded crimes are used by police forces to document community differences in crime and design spatially targeted strategies. Nevertheless, crimes known to police are affected by selection biases driven by underreporting. This paper presents a simulation study to analyze if crime statistics aggregated at small spatial scales are affected by larger bias than maps produced for larger geographies. Based on parameters obtained from the UK Census, we simulate a synthetic population consistent with the characteristics of Manchester. Then, based on parameters derived from the Crime Survey for England and Wales, we simulate crimes suffered by individuals, and their likelihood to be known to police. This allows comparing the difference between all crimes and police-recorded incidents at different scales. Measures of dispersion of the relative difference between all crimes and police-recorded crimes are larger when incidents are aggregated to small geographies. The percentage of crimes unknown to police varies widely across small areas, underestimating crime in certain places while overestimating it in others. Micro-level crime analysis is affected by a larger risk of bias than crimes aggregated at larger scales. These results raise awareness about an important shortcoming of micro-level mapping, and further efforts are needed to improve crime estimates.

/pdf/the-accuracy-of-crime-statistics-assessing-the-impact-of-2mwzrnhm4y.pdf

Samuel Langton

Papers

Six months in: pandemic crime trends in England and Wales

Residential burglary target selection: An analysis at the property-level using Google Street View

The accuracy of crime statistics: assessing the impact of police data bias on geographic crime analysis

Residential burglary target selection: an analysis at the property-level

Small area variation in crime effects of COVID-19 policies in England and Wales