gov3009-l October 2010

gov3009-l@lists.fas.harvard.edu

1 participants
4 discussions

Graif on "The Spatial Embeddedness of Neighborhood Effects"

by Matt Blackwell

Hi all, We hope that you can join us for the Applied Statistics Workshop this Wednesday, October 27th when we will be happy to have Corina Graif, a PhD candidate in the Sociology department giving a practice job talk entitled "The Spatial Embeddedness of Neighborhood Effects: Toward a Spatial Understanding of Mental Health and Obesity in the Context of Moving to Opportunity." You will find an abstract below. As always, we will serve a light lunch (Thai) and the talk will begin around 12:15p. "The Spatial Embeddedness of Neighborhood Effects: Toward a Spatial Understanding of Mental Health and Obesity in the Context of Moving to Opportunity" Corina Graif Department of Sociology CGIS K354 (1737 Cambridge St.) Wednesday, October 27th, 12 noon Abstract: This chapter makes the case that locational attainment and neighborhood effects cannot be fully understood outside the larger spatial context within which neighborhoods are embedded. The importance of neighborhood poverty in stifling residents’ physical and mental wellbeing has long been recognized by social scientists and policy makers. While heated debates across the disciplines reignite periodically about the adequate measurement of neighborhoods, this paper breaks away from the aggregation-level dilemma to consider alternative understandings of place and space. Analyses are based on longitudinal data on over 4000 low-income families who participated in the Moving to Opportunity Experiment in five major U.S. cities. The findings support the hypothesis that the spatial context of neighborhoods matters for mental health and obesity. Moreover, they indicate that the environmental factors affecting obesity tend to be more spatially localized while those affecting mental health tend to be spatially expansive. The spatial framework for thinking about neighborhood effects proposed here allows for a more nuanced integration with the differential spatial distributions of resources and disadvantage within and across cities and bears critical implications for reorienting the discussions of locational attainment and neighborhood effects toward a more continuous consideration of the role of space and its interaction with place. Cheers, matt. ~~~~~~~~~~~ Matthew Blackwell PhD Candidate Institute for Quantitative Social Science Department of Government Harvard University url: http://people.fas.harvard.edu/~blackwel/

13 years, 6 months

Wittenberg on “Without Rhyme or Reason? Explaining Pogroms in Poland”

by Matt Blackwell

Hi all, We hope that you can join us at the Applied Statistics Workshop this Wednesday, October 20th when we're excited to have Jason Wittenberg presenting applied work on anti-Jewish pogroms in Poland during World War II. Jason is an Assistant Professor of Political Science at the University of California, Berkeley. He is looking forward to getting feedback on the statistical issues in his work, which is joint with Jeffrey Kopstein at the University of Toronto. Attached you will find two draft book chapters: first, a broad introduction to the subject and second, a chapter describing the empirical results. As this research is still under development, we ask that you refer to Jason first before circulating these drafts. We will serve a light lunch (sandwiches). "Without Rhyme or Reason? Explaining Pogroms in Poland" Jason Wittenberg Department of Political Science, University of California, Berkeley Wednesday, October 20th, 12 noon CGIS K354 (1737 Cambridge St) Description: Two tragedies befell the Jews of Eastern Europe after the outbreak of World War II. The first and by far the best known and exhaustively researched is the Shoah, the Nazi extermination effort. The second, as Zbikowski (1993: 174) eloquently puts it, is “the violent explosion of the latent hatred and hostility of local communities.” This book focuses on the second tragedy, a wave of popular anti-Jewish violence that erupted in summer 1941, in the aftermath of the Nazi invasion of the Soviet Union. Why did pogroms occur in some localities but not others? This is our central question. Our results demonstrate that many of the most commonly believed explanations for pogroms do not hold up to empirical scrutiny. The 1941 pogroms were not orchestrated by the state, and did not occur where economic competition between Jews and non-Jews was fiercest, where anti-Semitism was most virulent, or where Jews were the most sympathetic to communism. None of these accounts explain the relative rarity of the violence. We contend that the pogroms were ultimately about politics. They represented a strategy whereby non-Jews, in Poland principally Poles and Ukrainians, attempted to rid themselves of what they thought would be future political rivals. Cheers, matt. ~~~~~~~~~~~ Matthew Blackwell PhD Candidate Institute for Quantitative Social Science Department of Government Harvard University url: http://people.fas.harvard.edu/~blackwel/

13 years, 6 months

Onnela on "Community structure in time-dependent, multiscale, and multiplex networks"

by Matt Blackwell

Hi all, We hope that you can join us at the Applied Statistics Workshop this Wednesday, October 13th when we're excited to have Jukka-Pekka Onnela presenting on community structures in networks. JP is a Postdoctoral Research Fellow at the Harvard Medical School, where he works on theoretical and applied problems with large-scale social and health networks. This talk will be based on work recently published in Science. You will find an abstract and a link to the paper below. A light lunch (Thai) will be provided. "Community structure in time-dependent, multiscale, and multiplex networks" Jukka-Pekka Onnela Harvard Medical School Wednesday, October 13th, 12 noon CGIS K354 (1737 Cambridge St) Abstract: During the last decade, the science of networks has grown into an enormous interdisciplinary endeavor, with methods and applications drawn from across the natural, social, and information sciences. One of the most important and prominent ideas from network science is the algorithmic detection of tightly-connected groups of nodes known as communities. Here we develop a formulation to detect communities in a very broad setting by studying general dynamical processes on networks. We create a new framework of network quality functions that allows us to study the community structure of arbitrary multislice networks, which are combinations of individual networks coupled through additional links that connect each node in one network slice to itself in other slices. This new framework allows one for the first time to study community structure in a very general setting that encompasses networks that evolve in time, have multiple types of ties (multiplexity), and have multiple scales. Paper: http://jponnela.com/web_documents/a25.pdf Cheers, matt. ~~~~~~~~~~~ Matthew Blackwell PhD Candidate Institute for Quantitative Social Science Department of Government Harvard University url: http://people.fas.harvard.edu/~blackwel/

13 years, 6 months

Ramey on "How GPUs Can Help Solve Large Optimization Problems"

by Matt Blackwell

Hi all, We hope you can join us for the Applied Statistics Workshop this Wednesday, October 6th, when we will be happy to have Adam Ramey, who is currently a Statistician/Analyst at the Harvard Business School, presenting a talk on utilizing graphical processing units for large optimization problem. You will find details about the talk and an abstract below. We will serve lunch (sandwiches) at the workshop. Hope you can make it. "Graphic Materiel: How GPUs Can Help Solve Large Optimization Problems." Adam Ramey Harvard Business School October 6th, 2010, 12 noon K354 CGIS Knafel (1737 Cambridge St) Abstract: The advent of multi-core processing has led to the implementation of explicit and implicit multithreading in most modern statistical packages. Unfortunately, in many of these cases, the user is required to "hard code" how the processes are to be divided up across multiple cores. Perhaps more problematic, the utility of this parallelization is restricted by the number of threads/cores in a user's machine. To address this issue in a cost-effective way, GPU computing has emerged as a powerful alternative. Harnessing the power of hundreds of small cores, GPU's are able to parallelize at a level virtually impossible in a CPU framework. In this talk, I discuss how MATLAB and R can take advantage of the GPU and present Monte Carlo experiments verifying the sheer power of the method. ~~~~~~~~~~~ Matthew Blackwell PhD Candidate Institute for Quantitative Social Science Department of Government Harvard University url: http://people.fas.harvard.edu/~blackwel/

13 years, 6 months

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gov3009-l October 2010