Do Sports Programs Prevent Crime and Reduce Reoffending? A Systematic Review and Meta-Analysis on the Effectiveness of Sports Programs

Objectives Sports programs are widely implemented as measures of crime prevention. In contrast to their popularity, there is little systematic knowledge about their effectiveness. This systematic review and meta-analysis have been carried out to fill this gap. In a systematic review, we gathered data on evaluated prevention programs specifically designed to prevent crime and delinquency. We then conducted a meta-analytic integration with studies using at least roughly equivalent control groups for the program evaluation. Method To retrieve relevant literature, we conducted a comprehensive international literature search until June 2021 drawing on scientific databases. We also applied snow-balling searches and contacted practitioners in the field. Studies were eligible if they evaluated sports programs designed to prevent delinquency on primary, secondary, and/or tertiary level. We focused on crime-related outcomes and potentially underlying psycho-social factors. We made no restrictions regarding characteristics of the participants or other aspects such as duration of the program. Results 24 studies were eligible for our systematic review, from which only thirteen were included into our meta-analytic integration. We found a moderate effect of participation in sports programs on crime-related outcomes (d = 0.36, p < .001). Participants showed a significant decrease in outcomes such as aggressiveness or anti-social behavior. We also analyzed psychological outcomes such as self-esteem or mental well-being, which also significantly improved when participating in sports programs (d = 0.87, p < ..05). Conclusions Sports programs seem to be an effective measure of crime prevention. However, future research needs more sound evaluation designs and moderator analyses to better understand the functioning and improve the implementation of sports programs.

A new vertically integrated, MOno-Layer Higher-Order ice flow model (MOLHO)

Numerical simulations of ice sheets rely on the momentum balance to determine how ice velocities change as the geometry of the system evolves. Ice is generally assumed to follow a Stokes flow with a nonlinear viscosity. Several approximations have been proposed in order to lower the computational cost of a full-Stokes stress balance. A popular option is the Blatter-Pattyn or Higher-Order model (HO), which consists of a three-dimensional set of equations that solves the horizontal velocities only. However, it still remains computationally expensive for long transient simulations. Here we present a depth-integrated formulation of the HO model, which can be solved on a two-dimensional mesh in the horizontal plane. We employ a specific polynomial function to describe the vertical variation of the velocity, which allows us to integrate the vertical dimension using a semi-analytic integration. We assess the performance of this MOno-Layer Higher-Order model (MOLHO) to compute ice velocities and simulate grounding line dynamics on standard benchmarks (ISMIP-HOM and MISMIP3D). We compare MOLHO results to the ones obtained with the original three-dimensional HO model. We also compare the time performance of both models in time-dependent runs. Our results show that the ice velocities and grounding line positions obtained with MOLHO are in very good agreement with the ones from HO. In terms of computing time, MOLHO requires less than 10 % of the computational time of a typical HO model, for the same simulations. These results suggest that the MOno-Layer Higher-Order formulation provides improved computational time performance and a comparable accuracy compared to the HO formulation, which opens the door to Higher-Order paleo simulations.

Analytic Integration of the Newton Potential over Cuboids and an Application to Fast Multipole Methods

We present simplified formulæ for the analytic integration of the Newton potential of polynomials over boxes in two- and three-dimensional space. These are implemented in an easy-to-use C++ library that allows computations in arbitrary precision arithmetic which is also documented here. We describe how these results can be combined with fast multipole methods to evaluate the Newton potential of more general, non-polynomial densities.

The Evolution of Resource-Based Inquiry: A Review and Meta-Analytic Integration of the Strategic Resources–Actions–Performance Pathway

Understanding why some firms outperform others is central to strategy research. The resource-based view (RBV) suggests that competitive advantages arise due to possessing strategic resources (i.e., assets that are valuable, rare, nonsubstitutable, and inimitable), and researchers have extended this logic to explain performance differences. However, RBV is relatively silent about the actions managers could use to create or capitalize on a resource-based advantage. Enriching RBV, the resource orchestration framework describes specific managerial actions that use such resources to realize performance gains. After reviewing the conceptual evolution of these two literature streams as well as related streams, we use meta-analytic structural equation modeling to aggregate evidence from 255 samples involving 111,614 observations to answer outstanding research questions regarding the strategic resources–actions–performance pathway. The results show strong complementarity and interdependence between their logics. Additional inquiry drawing on their complementarity is a clear path toward enhancing scholars’ understanding of how and why some firms outperform others. We build on our findings to lay a foundation for such inquiry, including a call for theorizing centered on the interdependence of resources and actions, as well as new theoretical terrain that can help resource-based inquiry continue to evolve.

Integrating Without Quantitizing: Two Examples of Deductive Analysis Strategies Within Qualitatively Driven Mixed Methods Research

When mixed methods research (MMR) has a qualitatively driven analytic frame, integration techniques should align with the purposes and contributions of qualitative methods. This article describes two integration strategies that can be used within qualitatively driven MMR to deductively analyze qualitative data: (a) using quantitative variables as a coding framework, (b) using statistical findings to develop codes for qualitative analysis. The strategies capitalize on the strengths of qualitatively driven MMR while facilitating analytic integration. After describing the strategies, we provide examples within a study examining early childhood inclusive education. This discussion contributes to MMR by providing integration strategies that are necessarily grounded in an analytic frame and that allow rigorous qualitative analysis, facilitate systematic analytic integration, and promote richer understanding of phenomena.

Analytic integration of soft and collinear radiation in factorised QCD cross sections at NNLO

Within the framework of local analytic sector subtraction, we present the full analytic integration of double-real and real-virtual local infrared counterterms that enter NNLO QCD computations with any number of massless final-state partons. We show that a careful choice of phase-space mappings leads to simple analytic results, including non-singular terms, that can be obtained with conventional integration techniques.

IBP reduction coefficients made simple

We present an efficient method to shorten the analytic integration-by-parts (IBP) reduction coefficients of multi-loop Feynman integrals. For our approach, we develop an improved version of Leinartas’ multivariate partial fraction algorithm, and provide a modern implementation based on the computer algebra system Singular. Furthermore, we observe that for an integral basis with uniform transcendental (UT) weights, the denominators of IBP reduction coefficients with respect to the UT basis are either symbol letters or polynomials purely in the spacetime dimension D. With a UT basis, the partial fraction algorithm is more efficient both with respect to its performance and the size reduction. We show that in complicated examples with existence of a UT basis, the IBP reduction coefficients size can be reduced by a factor of as large as ∼ 100. We observe that our algorithm also works well for settings without a UT basis.