Routine activities and proactive police activity: a macro-scale analysis of police searches in London and New York City

This paper explored how city-level changes in routine activities were associated with changes in frequencies of police searches using six years of police records from the London Metropolitan Police Service and the New York City Police Department. Routine activities were operationalised through selecting events that potentially impacted on (a) the street population, (b) the frequency of crime or (c) the level of police activity. OLS regression results indicated that routine activity variables (e.g. day of the week, periods of high demand for police service) can explain a large proportion of the variance in search frequency throughout the year. A complex set of results emerged, revealing cross-national dissimilarities and the differential impact of certain activities (e.g. public holidays). Importantly, temporal frequencies in searches are not reducible to associations between searches and recorded street crime, nor changes in on-street population. Based on the routine activity approach, a theoretical police-action model is proposed

Long and short paths in uniform random recursive dags

In a uniform random recursive k-dag, there is a root, 0, and each node in turn, from 1 to n, chooses k uniform random parents from among the nodes of smaller index. If S_n is the shortest path distance from node n to the root, then we determine the constant \sigma such that S_n/log(n) tends to \sigma in probability as n tends to infinity. We also show that max_{1 \le i \le n} S_i/log(n) tends to \sigma in probability.Comment: 16 page

Varieties of increasing trees

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Applying neighbourhood classification systems to natural hazards: a case study of Mt Vesuvius

The dynamic forces of urbanisation that characterised much of the 20th Century and still dominate population growth in developing countries have led to the increasing risk of natural hazards in cities around the world (Chester 2000, Pelling 2003). None of these physical dangers is more tangible than the threat volcanoes pose to the large populations living in close proximity. Vesuvius, a recognised decade volcano following the UN’s International Decade for Natural Disaster Reduction (IDNDR) has an estimated 550,000 people that live in areas susceptible to Pyroclastic Density Currents (PDC) (Barberi 2008) and a further 4 million at risk from ash fallout around the sprawling suburbs of Naples. Though quiescent since 1944, the prospect of a large eruption of Vesuvius presents a greater geophysical threat to the Campania region of Italy than perhaps ever before. With the Neopolitan region at risk from such an event, this paper proposes a new methodology for creating a Social Vulnerability Index (SoVi) using geodemographic classification systems. In this study, Experian’s MOSAIC Italy database is combined with geophysical risk boundaries to assess the overall vulnerability of the population around Vesuvius