Objectives: This paper uses transportation data to estimate how daily spatio-temporal shifts in population influence the distribution of crime over a city's census tracts (CTs). A "funnel hypothesis" states that these daily flows are central for crime concentrations within a city. We present arguments for and against funneling prior to empirical analysis.Methods: A municipal transport agency in a large city in Eastern Canada surveyed 66,100 households about daily trips for work, shopping, recreation, and school. This allowed us to link inflows of visitors to numbers of property and violent crimes for 506 CTs. Results:We find strong support for a funneling effect. Daily visitors have a major impact on distributions over this city for both violent and property crimes. Conclusions:Daily spatio-temporal shifts could be significantly more important than fixed residential factors for distributing crime over urban space.

For security and justice professionals (e.g., police officers, lawyers, judges), the thousands of peer-reviewed articles on nonverbal communication represent important sources of knowledge. However, despite the scope of the scientific work carried out on this subject, professionals can turn to programs, methods, and approaches that fail to reflect the state of science. The objective of this article is to examine (i) concepts of nonverbal communication conveyed by these programs, methods, and approaches, but also (ii) the consequences of their use (e.g., on the life or liberty of individuals). To achieve this objective, we describe the scope of scientific research on nonverbal communication. A program (SPOT; Screening of Passengers by Observation Techniques), a method (the BAI; Behavior Analysis Interview) and an approach (synergology) that each run counter to the state of science are examined. Finally, we outline five hypotheses to explain why some organizations in the fields of security and justice are turning to pseudoscience and pseudoscientific techniques. We conclude the article by inviting these organizations to work with the international community of scholars who have scientific expertise in nonverbal communication and lie (and truth) detection to implement evidence-based practices. Análisis de la comunicación no verbal: los peligros de la pseudociencia en entornos de seguridad y justicia R E S U M E N Para los profesionales de la seguridad y la justicia (policías, abogados, jueces), los miles de artículos revisados por pares sobre comunicación no verbal representan fuentes importantes de conocimiento. Sin embargo, a pesar del alcance del trabajo científico realizado sobre este tema, los profesionales pueden recurrir a programas, métodos y enfoques que no reflejan el estado real de la ciencia. El objetivo de este artículo es examinar (i) los conceptos de comunicación no verbal transmitidos por estos programas, métodos y enfoques, pero también (ii) las consecuencias de su uso (por ejemplo, sobre la vida o la libertad de las personas). Para lograr estos objetivos, describimos el alcance de la investigación científica sobre la comunicación no verbal. Se examina un programa (SPOT: Evaluación de pasajeros mediante técnicas de observación), un método (BAI: Entrevista de análisis de conducta) y un enfoque (sinergología) que contradicen el estado de la ciencia. Finalmente, presentamos cinco hipótesis para explicar por qué algunas organizaciones en los campos de la seguridad y la justicia están recurriendo a la pseudociencia y a las técnicas pseudocientíficas. Concluimos el artículo invitando a estas organizaciones a trabajar con la comunidad académica internacional especializada en la investigación sobre comunicación no verbal y detección de mentiras (y verdad) para implementar prácticas basadas en la evidencia.

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This article examines the effect that collective bargaining had on official crime statistics compiled between 1998 and 2009 in Montreal, Canada. Police officers collectively decided to reduce their use of record-discretion on two occasions, to increase administrative workload and pressure their employers. Considerable increases of recorded assaults and mischief were observed, despite no apparent variation of reported infractions measured by calls for service. Recorded and reported car thefts and burglaries displayed no significant variation. Results suggest that observed variations can be explained in terms of temporary differential treatment of specific incidents rather than increases of reported criminality or proactive police activity. This research challenges the reliability of official statistics as measures of crime and demonstrates that external circumstances can influence police recording practices.

Research shows that co-offending has contradictory effects on rates of re-arrest. On the one hand, group offending may be riskier: for example, co-offenders might be targeted by police or might snitch to protect themselves. Criminal networks may also have indirect effects: offenders embedded in criminal networks commit more offenses and thus should have a higher risk of being arrested at some point. On the other hand, networks generate steady criminal opportunities with relatively low risk of arrest and high monetary benefits (e.g., drug trafficking). Few authors have empirically explored the relation between co-offending and re-arrest. This paper does so, using data from seven years of arrest records in the province of Quebec (Canada). The analysis is designed to explore why some offenders are re-arrested after an initial arrest while others are not. It focuses on the factors involved in re-arrest, considering two distinct levels of measures of co-offending. The first level of analysis takes into account a situational measure that indicates whether a given offense was committed by co-offenders (group offense). The second level is used to examine whether being part of a criminal network influences re-arrest. For offenders embedded in such networks, two network features (degree centrality and clustering coefficient) show that the global position of individuals within the Quebec arrest network are analyzed. Our results suggest that co-offending is a crucial factor that should be taken into account when looking at the odds of being caught again. The use of generalized linear mixed model brings interesting nuances about the impact of co-offending. The paper adds to the recently growing literature on the link between networks and criminal careers.