City Year: Year 1 Evaluation Report, 2013-2014

City Year is an education-focused nonprofit organization that partners with high needs public schools to enhance the quality of the learning environment in the areas of attendance, behavior, and course performance. This is achieved by deploying teams of City Year corps members to the schools. The expectation is that students who receive support from City Year corps members in the areas of English, math, attendance, and behavior will show growth in their academic and behavioral outcomes. With funding from the William Penn Foundation, City Year is being implemented in 11 high needs public schools within The School District of Philadelphia (SDP or District); targeted support is provided to at-risk students in grades 6 to 9. The Office of Research and Evaluation (ORE) is currently evaluating City Year's effectiveness in meeting the above goals for the 2013-2014 school year (SY) – Year 1— and extending into the 2014-2015 SY – Year 2

A multi-paradigm language for reactive synthesis

This paper proposes a language for describing reactive synthesis problems that integrates imperative and declarative elements. The semantics is defined in terms of two-player turn-based infinite games with full information. Currently, synthesis tools accept linear temporal logic (LTL) as input, but this description is less structured and does not facilitate the expression of sequential constraints. This motivates the use of a structured programming language to specify synthesis problems. Transition systems and guarded commands serve as imperative constructs, expressed in a syntax based on that of the modeling language Promela. The syntax allows defining which player controls data and control flow, and separating a program into assumptions and guarantees. These notions are necessary for input to game solvers. The integration of imperative and declarative paradigms allows using the paradigm that is most appropriate for expressing each requirement. The declarative part is expressed in the LTL fragment of generalized reactivity(1), which admits efficient synthesis algorithms, extended with past LTL. The implementation translates Promela to input for the Slugs synthesizer and is written in Python. The AMBA AHB bus case study is revisited and synthesized efficiently, identifying the need to reorder binary decision diagrams during strategy construction, in order to prevent the exponential blowup observed in previous work.Comment: In Proceedings SYNT 2015, arXiv:1602.0078

Hysteresis and unemployment : a preliminary investigation

This paper points out what hysteresis is using a simple model of market entry and exit. A procedure for calculating hysteresis indices for economic time series is outlined. Some preliminary results are presented to assess the explanatory power of hysteresis variables with regard to the equilibrium rate of unemployment in the UK. We find that both natural and "unnatural" variables enter a cointegrating vector for UK unemployment 1959-1996. The natural variable is the replacement ratio. The 'unnatural' variables are the hysteresis index of the exchange rate; and hysteresis indices for the real oil price and the real interest rate

CHOICE AND TEMPORAL WELFARE IMPACTS: DYNAMIC GEV DISCRETE CHOICE MODELS

Welfare economics is often employed to measure the impact of economic policies or externalities. When demand is characterized by discrete choices, static models of consumer demand are employed for this type of analysis because of the difficulty in estimating dynamic discrete choice models. In this paper we provide a tractable approach to estimating dynamic discrete choice models of the Generalized Extreme Value (GEV) family that addresses many of the problems identified in the literature and provides a rich set of parameters describing dynamic choice. We apply this model to the case of recreational fishing site choice, comparing dynamic to static versions. In natural resource damage assessment cases, static discrete choice models of recreational site choice are often employed to calculate welfare measures, which will be biased if the underlying preferences are actually dynamic in nature. In our empirical case study we find that the dynamic model provides a richer behavioral model of site choice, and reflects the actual choices very well. We also find significant differences between static and dynamic welfare measures. However, we find that the dynamic model raises several concerns about the specification of the policy impact and the subsequent welfare measurement that are not raised in static cases.Demand and Price Analysis,

Educational commitment and social networking: The power of informal networks

The lack of an engaging pedagogy and the highly competitive atmosphere in introductory science courses tend to discourage students from pursuing science, technology, engineering, and mathematics (STEM) majors. Once in a STEM field, academic and social integration has been long thought to be important for students' persistence. Yet, it is rarely investigated. In particular, the relative impact of in-class and out-of-class interactions remains an open issue. Here, we demonstrate that, surprisingly, for students whose grades fall in the "middle of the pack," the out-of-class network is the most significant predictor of persistence. To do so, we use logistic regression combined with Akaike's information criterion to assess in- and out-of-class networks, grades, and other factors. For students with grades at the very top (and bottom), final grade, unsurprisingly, is the best predictor of persistence---these students are likely already committed (or simply restricted from continuing) so they persist (or drop out). For intermediate grades, though, only out-of-class closeness---a measure of one's immersion in the network---helps predict persistence. This does not negate the need for in-class ties. However, it suggests that, in this cohort, only students that get past the convenient in-class interactions and start forming strong bonds outside of class are or become committed to their studies. Since many students are lost through attrition, our results suggest practical routes for increasing students' persistence in STEM majors.Comment: 12 pages, 2 figures, 8 tables, 6 pages of Supplementary Material

Community-Based Production of Open Source Software: What Do We Know About the Developers Who Participate?

This paper seeks to close an empirical gap regarding the motivations, personal attributes and behavioral patterns among free/libre and open source (FLOSS) developers, especially those involved in community-based production, and its findings on the existing literature and the future directions for research. Respondents to an extensive web-survey’s (FLOSS-US 2003) questions about their reasons for work on FLOSS are classified according to their distinct “motivational profiles” by hierarchical cluster analysis. Over half of them also are matched to projects of known membership sizes, revealing that although some members from each of the clusters are present in the small, medium and large ranges of the distribution of project sizes, the mixing fractions for the large and the very small project ranges are statistically different. Among developers who changed projects, there is a discernable flow from the bottom toward the very small towards to large projects, some of which is motivated by individuals seeking to improve their programming skills. It is found that the profile of early motivation, along with other individual attributes, significantly affects individual developers’ selections of projects from different regions of the size range.Open source software, FLOSS project, community-based peer production, population heterogeneity, micro-motives, motivational profiles, web-cast surveys, hierarchical cluster analysis