Assessing the Spatial Connection between Urban Agriculture and Equity

This paper investigates the relationship between spatial planning and urban agriculture (UA) – primarily community gardens and market farms – through an equity lens. Significant research has been done on the benefits and challenges associated with UA, focusing on community food security, social justice, and community development; however, the spatial distribution of UA projects and the relationship between their form and the fabric of the urban built environment requires additional research. Using data from the City of Philadelphia, this paper explores two questions. First, what is the spatial relationship between UA-projects and food-insecure neighbourhoods? Second, how does UA form and landscape fit within the urban built environment? Answering the first question involved GIS-based spatial analysis and statistical tests to explore the relationship between UA access and areas with high food insecurity. Answering the second question led to the development of a spatial-typology of UA projects based upon GIS analysis and a qualitative visual inspection process, allowing for discussion on how various forms of UA fit within urban landscapes. Results show that siting UA projects may lead to spatial mismatch issues, and most unstable or temporary UA projects are located in high food-insecure neighbourhoods. By exploring the connections between urban food production, land use, spatial planning, and the built environment, the design of more equitable urban spaces may be achieved

Bermuda Civil Society Project: Analysis of Social Service Agencies

Offers a research synthesis on Bermuda's nonprofit sector, including trends and challenges, landscape, and snapshots of the health, education, workforce, and youth violence issue areas; an analysis of agency priorities and data; and recommendations

Determinants of quality, latency, and amount of Stack Overflow answers about recent Android APIs.

Stack Overflow is a popular crowdsourced question and answer website for programming-related issues. It is an invaluable resource for software developers; on average, questions posted there get answered in minutes to an hour. Questions about well established topics, e.g., the coercion operator in C++, or the difference between canonical and class names in Java, get asked often in one form or another, and answered very quickly. On the other hand, questions on previously unseen or niche topics take a while to get a good answer. This is particularly the case with questions about current updates to or the introduction of new application programming interfaces (APIs). In a hyper-competitive online market, getting good answers to current programming questions sooner could increase the chances of an app getting released and used. So, can developers anyhow, e.g., hasten the speed to good answers to questions about new APIs? Here, we empirically study Stack Overflow questions pertaining to new Android APIs and their associated answers. We contrast the interest in these questions, their answer quality, and timeliness of their answers to questions about old APIs. We find that Stack Overflow answerers in general prioritize with respect to currentness: questions about new APIs do get more answers, but good quality answers take longer. We also find that incentives in terms of question bounties, if used appropriately, can significantly shorten the time and increase answer quality. Interestingly, no operationalization of bounty amount shows significance in our models. In practice, our findings confirm the value of bounties in enhancing expert participation. In addition, they show that the Stack Overflow style of crowdsourcing, for all its glory in providing answers about established programming knowledge, is less effective with new API questions

How explicable are differences between reviews that appear to address a similar research question? A review of reviews of physical activity interventions

Background Systematic reviews are promoted as being important to inform decision-making. However, when presented with a set of reviews in a complex area, how easy is it to understand how and why they may differ from one another? Methods An analysis of eight reviews reporting evidence on effectiveness of community interventions to promote physical activity. We assessed review quality and investigated overlap of included studies, citation of relevant reviews, consistency in reporting, and reasons why specific studies may be excluded. Results There were 28 included studies. The majority (n = 22; 79%) were included only in one review. There was little cross-citation between reviews (n = 4/28 possible citations; 14%). Where studies appeared in multiple reviews, results were consistently reported except for complex studies with multiple publications. Review conclusions were similar. For most reviews (n = 6/8; 75%), we could explain why primary data were not included; this was usually due to the scope of the reviews. Most reviews tended to be narrow in focus, making it difficult to gain an understanding of the field as a whole. Conclusions In areas where evaluating impact is known to be difficult, review findings often relate to uncertainty of data and methodologies, rather than providing substantive findings for policy and practice. Systematic ‘maps’ of research can help identify where existing research is robust enough for multiple in-depth syntheses and also show where new reviews are needed. To ensure quality and fidelity, review authors should systematically search for all publications from complex studies. Other relevant reviews should be searched for and cited to facilitate knowledge-building

Robust Computer Algebra, Theorem Proving, and Oracle AI

In the context of superintelligent AI systems, the term "oracle" has two meanings. One refers to modular systems queried for domain-specific tasks. Another usage, referring to a class of systems which may be useful for addressing the value alignment and AI control problems, is a superintelligent AI system that only answers questions. The aim of this manuscript is to survey contemporary research problems related to oracles which align with long-term research goals of AI safety. We examine existing question answering systems and argue that their high degree of architectural heterogeneity makes them poor candidates for rigorous analysis as oracles. On the other hand, we identify computer algebra systems (CASs) as being primitive examples of domain-specific oracles for mathematics and argue that efforts to integrate computer algebra systems with theorem provers, systems which have largely been developed independent of one another, provide a concrete set of problems related to the notion of provable safety that has emerged in the AI safety community. We review approaches to interfacing CASs with theorem provers, describe well-defined architectural deficiencies that have been identified with CASs, and suggest possible lines of research and practical software projects for scientists interested in AI safety.Comment: 15 pages, 3 figure

School Finance Toolkit: How to Create a Community Guide to Your School District's Budget

If your community-based organization would like to launch a school finance initiative in your community, you can use this toolkit as a starting point. The toolkit walks through the major steps organizations have gone through in their own initiatives, offering advice and examples of tools you can adapt for your own use. The toolkit explores the major challenges organizations have faced in this work, and how they have addressed those challenges. And the toolkit points you toward other resources that can help you find and analyze information about school finance. This toolkit is not itself a primer on school finance. Except in passing, it does not explain how school funding works in school districts. You will have to obtain this kind of background information from other resources (some listed in this toolkit) and as you go along.The toolkit contains five major sections:Get Started. This section helps you set a mission for your school finance initiative, organize your people to get the job done, and find the resources to get the job done.Engage the Public. This section discusses strategies for engaging the public up-front, finding out what citizens want to know about school finance -- and why.Crunch the Numbers. This section addresses the nitty-gritty work of creating a community guide to the school budget, offering helpful tips on finding, analyzing, and presenting information effectively.Put the Numbers to Work. This section talks about ways you can use the information you have gathered as a catalyst for community-wide discussions of school finance and its impact on school quality.Resources. This section contains a variety of tools used by community-based organizations in their school finance initiatives, everything from town meeting agendas to focus group questions to budget analysis spreadsheets. This section also contains references to many sources of data about school finance, many of them just a mouse-click or toll-free call away