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610 days ago
Unfiled. Edited by Darron Fuller 610 days ago
  • As of Feb. 26, 2016, Washington, DC's unemployment rate was 6.6%, 48th in the nation (Source: BLS). 
  • Idea: Connect skilled workers of high unemployment/low economic geographic areas (census tracts) to opportunities in areas of high-opportunity.
  • Take-away: Unemployed workers may need to travel long distances to obtain work in high opportunity areas. This project pairs workers with jobs in order to maximize income after commuting expense. The results should inform transit decisions for DC. 
  • Steps: 
  • Used this info to identify high underutilization tracts (unemployment >= 10%) and high opportunity tracts (areas where there are more jobs than people living in the area).
  • We passed this info along to our Operations Research/Prescriptive Analytics team to run their optimization model built in Gurobi Optimizer to determine the optimal job paths with the goal of maximizing profit to underemployed/unemployed tracts (i.e., Profit = Expected Revenue from job less the Estimated cost for transportation and Estimated travel time * Expected wage rate).  They used number of people unemployed in a tract as the source number and number of available jobs (computed using 6% (our estimate of the national unemployment rate) times the number of jobs, which is a really rough estimate).  

261 days ago
Unfiled. Edited by Ryan Thomas 261 days ago
  • var width = 600
  • var height = 400
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  •     .attr('width', width)
  •     .attr('height', height)
581 days ago
Unfiled. Edited by Sophia Liu 581 days ago
Hacks from Open Data Day DC 2016
581 days ago
Unfiled. Edited by Eneshal Miller 581 days ago
This pad text is synchronized as you type, so that everyone viewing this page sees the same text.  This allows you to collaborate seamlessly on documents!
585 days ago
Unfiled. Edited by Joseph Cureton 585 days ago
  • Workshops (Saturday)
613 days ago
Unfiled. Edited by jalbertbowdenii 613 days ago
  • the trello board says it is private...how does one get access?
Darron F If the data is available, we would like to improve the model to support job and opportunity matching at the skills level and have more detail of specific jobs.  This approach should result in a better "fit" between tracts (or blocks) of low-employment and tracts offering opportunity and provide an enhanced decision management tool for city officials.  Furthermore this profit-maximizing framework can be extended down to the automated decisioning of matching job seekers directly to employers with available jobs.  Update 4/20/16:  Began working with the American Time Use Survey (ATUS) which asks respondents to provide details into their daily activities as well as their employment status.  The ATUS has specific questions regarding Employment and Underemployment and also could be used to better understand the skills of the respondents based upon the data of their logged activities.
638 days ago
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Unfiled. Edited by Rich Kucera 638 days ago
  • Rich Kucera -- System Configurator (GitHub: kucerarichard, kucerarichard@gmail.com)
639 days ago
Unfiled. Edited by Marla Parker 639 days ago
  • A useful consideration is using collaborative design thinking that involves users of the open data platform to be involved in actually creating it, which is another principle of good social innovation. May want to consider how citizens can contribute to the database
  • Look into partnering with Code2040.org
  • Important to highlight the socio-economic impact of recidvism
  • Highlight the failure of incarceration systems to do large scale, sustainable rehabilitation
  • Joseph Cureton Josephcureton1@gmail.com - Please contact me if interested in DC/Baltimore projects related to criminal justice reform. There are several slack channels and a mailing list through Rebuilding Reentry.
  • Marla Parker, marla.parker@asu.edu
Members (383)
Leah Hendey Yao Xiao Amanda Lopez Susan Bhattarai Eneshal Miller Darron Fuller John Jediny - XAAB Joshua Tauberer Christian Young Marla Parker Yue Liu Andre Shonubi Matthew Tringali Yunier Consuegra Stephen Larrick Michael Tran Evan Fischell Michael Sugimura Dennis Yau Nate Culwell-Kanarek

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