Partially identified treatment effects under imperfect compliance: the case of domestic violence

The Minneapolis Domestic Violence Experiment (MDVE) is a randomized social experiment with imperfect compliance which has been extremely influential in how police officers respond to misdemeanor domestic violence. This paper re-examines data from the MDVE, using recent literature on partial identification to find recidivism associated with a policy that arrests misdemeanor domestic violence suspects rather than not arresting them. Using partially identified bounds on the average treatment effect I find that arresting rather than not arresting suspects can potentially reduce recidivism by more than two-and-a-half times the corresponding intent-to-treat estimate and more than two times the corresponding local average treatment effect, even when making minimal assumptions on counterfactuals.

A modified PNN algorithm with optimal PD modeling using the orthogonal least squares method

In this paper a modified algorithm is suggested for developing polynomial neural network (PNN) models. Optimal partial description (PD) modeling is introduced at each layer of the PNN expansion, a task accomplished using the orthogonal least squares (OLS) method. Based on the initial PD models determined by the polynomial order and the number of PD inputs, OLS selects the most significant regressor terms reducing the output error variance. The method produces PNN models exhibiting a high level of accuracy and superior generalization capabilities. Additionally, parsimonious models are obtained comprising a considerably smaller number of parameters compared to the ones generated by means of the conventional PNN algorithm. Three benchmark examples are elaborated, including modeling of the gas furnace process as well as the iris and wine classification problems. Extensive simulation results and comparison with other methods in the literature, demonstrate the effectiveness of the suggested modeling approach.

An urban parameterization for a global climate model. Part I: Formulation and evaluation for two cities

Urbanization, the expansion of built-up areas, is an important yet less-studied aspect of land use/land cover change in climate science. To date, most global climate models used to evaluate effects of land use/land cover change on climate do not include an urban parameterization. Here, the authors describe the formulation and evaluation of a parameterization of urban areas that is incorporated into the Community Land Model, the land surface component of the Community Climate System Model. The model is designed to be simple enough to be compatible with structural and computational constraints of a land surface model coupled to a global climate model yet complex enough to explore physically based processes known to be important in determining urban climatology. The city representation is based upon the “urban canyon” concept, which consists of roofs, sunlit and shaded walls, and canyon floor. The canyon floor is divided into pervious (e.g., residential lawns, parks) and impervious (e.g., roads, parking lots, sidewalks) fractions. Trapping of longwave radiation by canyon surfaces and solar radiation absorption and reflection is determined by accounting for multiple reflections. Separate energy balances and surface temperatures are determined for each canyon facet. A one-dimensional heat conduction equation is solved numerically for a 10-layer column to determine conduction fluxes into and out of canyon surfaces. Model performance is evaluated against measured fluxes and temperatures from two urban sites. Results indicate the model does a reasonable job of simulating the energy balance of cities.

Climate and more sustainable cities: climate information for improved planning and management of cities (producers/capabilities perspective)

In the last two decades substantial advances have been made in the understanding of the scientific basis of urban climates. These are reviewed here with attention to sustainability of cities, applications that use climate information, and scientific understanding in relation to measurements and modelling. Consideration is given from street (micro) scale to neighbourhood (local) to city and region (meso) scale. Those areas where improvements are needed in the next decade to ensure more sustainable cities are identified. High-priority recommendations are made in the following six strategic areas: observations, data, understanding, modelling, tools and education. These include the need for more operational urban measurement stations and networks; for an international data archive to aid translation of research findings into design tools, along with guidelines for different climate zones and land uses; to develop methods to analyse atmospheric data measured above complex urban surfaces; to improve short-range, high-resolution numerical prediction of weather, air quality and chemical dispersion through improved modelling of the biogeophysical features of the urban land surface; to improve education about urban meteorology; and to encourage communication across scientific disciplines at a range of spatial and temporal scales.

Motivational, emotional, and behavioral correlates of fear of missing out

Social media utilities have made it easier than ever to know about the range of online or offline social activities one could be engaging. On the upside, these social resources provide a multitude of opportunities for interaction; on the downside, they often broadcast more options than can be pursued, given practical restrictions and limited time. This dual nature of social media has driven popular interest in the concept of Fear of Missing Out – popularly referred to as FoMO. Defined as a pervasive apprehension that others might be having rewarding experiences from which one is absent, FoMO is characterized by the desire to stay continually connected with what others are doing. The present research presents three studies conducted to advance an empirically based understanding of the fear of missing out phenomenon. The first study collected a diverse international sample of participants in order to create a robust individual differences measure of FoMO, the Fear of Missing Out scale (FoMOs); this study is the first to operationalize the construct. Study 2 recruited a nationally representative cohort to investigate how demographic, motivational and well-being factors relate to FoMO. Study 3 examined the behavioral and emotional correlates of fear of missing out in a sample of young adults. Implications of the FoMOs measure and for the future study of FoMO are discussed.

Cities��� low carbon plans in an ‘age of austerity’: an analysis of UK local authority actions, attitudes and responses

Background: Cities play a significant role globally in creating carbon emissions but, as centers of major population, innovation and social practice, they also offer important opportunities to tackle climate change. The new challenges faced by cities in an ‘age of austerity’ and decentralist agendas present substantial challenges for coordinated multilevel governance. Results: Based on research carried out in 2011–2012, this paper examines the attitudes and responses of sustainability and climate change officers in UK cities that have prepared low carbon and climate change plans, in the context of these challenges. Using a conceptual framework that analyses ‘awareness’, ‘analysis’ and ‘actions’ (in the context of spending cuts and a new ‘decentralized’ policy agenda) this research suggests that progress on low-carbon futures for cities continues to be fragmented, with increased funding constraints, short-termism and lack of leadership acting as key barriers to progress. Conclusion: Recent UK national policies (including localism, austerity measures and new economic incentives) have not only created further uncertainties, but also scope for cities��� local innovation through policy leverage and self-governing actions.

Healing the wounds of war: memories of violence and the making of history in Zimbabwe's most recent past.

How does a society less than two decades after a liberation war which involved large sections of the population come to terms with the memories of violence and war — a war in which there was no clear distinction between insurgent and counter‐insurgent, liberator and oppressor and in which the majority of the casualties can be found among the rural civilian population? This was a predicament not exclusive to Zimbabwe, but one which also applies to Mozambique, South Africa and, more recently, to Rwanda. Since its independence Zimbabwe has been a prime example of successful reconciliation. Ranger has argued that spiritual healing has contributed importantly to coming to terms with the trauma of war through turning violence into history. Here it will be argued that an analysis of the intersections between memories of violence, healing, and history reveals a twofold process. Social healing is made possible by a shift from conviction and compensation to revealing without convicting. At the same time healing provides an arena for communities in which competing and contesting memories of violence are renegotiated. Through these processes sense is being made of the past; history is being made.