Archive for the 'Data & Methods' Category

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Police calls and blurry neighborhood boundaries

Here’s a great piece using a mix of administrative data (complaint calls to the police), on-line forums, spatial data, and traditional census data to see what happens in the transition zones across neighborhoods. The first link is to the easy-to-read version as reported in CityLab; the second is the original piece, with more details about the methodology.

When Racial Boundaries Are Blurry, Neighbors Take Complaints Straight to 311
Laura Bliss | CityLab
August 25, 2015
In NYC, calls about noise and blocked driveways are most frequent in zones between racially homogenous neighborhoods.

Contested Boundaries: Explaining Where Ethno-Racial Diversity Provokes Neighborhood Conflict
Joscha Legewie and Merlin Schaeffer | Presentated at the American Sociological Meetings
August 21, 2015

Many Psychology Findings Not as Strong as Claimed

The New York Times reports a study published in the latest issue of Science. “A painstaking yearslong effort to reproduce 100 studies published in three leading psychology journals has found that more than half of the findings did not hold up when retested.”

Many Psychology Findings not as Strong as Claimed.

 

Raster Analysis in R

Etienne Racine has published a Visual Raster Cheat Sheet in RPubs.

H/T Urban Demographics.

Rules for Charts

Nathan Yau of Flowing Data discusses the handful of rules for charts and data visualization which should never be broken. These include baselines, pie slices, and encodings.

New York City Census FactFinder

The NYC Planning Department’s American Community Survey update to the NYC Census Factfinder application has been released. It is now possible to get 2009-2013 ACS profiles for Neighborhood Tabulation Areas and user defined census tract aggregations, in addition to demographic profiles from the 2000 and 2010 censuses.

See the full press release.

H/T Data Detectives

Cleaning Data and Extracting Data from PDFs

Flowing Data points out two useful data resources:

  • Marc Bellemare, an associate professor in the Department of Applied Economics at the University of Minnesota, provides practical tips on cleaning data.
  • Tabula, which is available for both Windows and Mac, has an update which makes it easier to extract data from PDF documents.

Using Probability in Criminal Sentencing

FlowingData extracts a statistics lesson on probability from a piece in FiveThirtyEight about risk assessment and criminal sentencing.

New Book From the Oxford Poverty & Human Development Initiative

The Oxford Poverty & Human Development Initiative published a book on Multidimensional Poverty Measurement & Analysis:

Multidimensional poverty measurement and analysis is evolving rapidly. Quite recently, a particular counting approach to multidimensional poverty measurement, developed by Sabina Alkire and James Foster, has created considerable interest. Notably, it has informed the publication of the Global Multidimensional Poverty Index (MPI) estimates in the Human Development Reports of the United Nations Development Programme since 2010, and the release of national poverty measures in Chile, Mexico, Colombia, Bhutan and the Philippines. The academic response has been similarly swift, with related articles published in both theoretical and applied journals.

The high and insistent demand for in-depth and precise accounts of multidimensional poverty measurement motivates this book, which is aimed at graduate students in quantitative social sciences, researchers of poverty measurement, and technical staff in governments and international agencies who create multidimensional poverty measures.

Draft chapters are available online.

Poll Results and Response Rates

Scott Keeter, Pew Research Center’s director of survey research, discusses declining response rates and what it means for survey reliability.

Big data and smart cities

Urban Demographics posted a presentation by Rob Kitchin based on his paper “The real-time city? Big data and smart urbanism” (gated version; working paper version).

Abstract:

‘Smart cities’ is a term that has gained traction in academia, business and government to describe cities that, on the one hand, are increasingly composed of and monitored by pervasive and ubiquitous computing and, on the other, whose economy and governance is being driven by innovation, creativity and entrepreneurship, enacted by smart people. This paper focuses on the former and, drawing on a number of examples, details how cities are being instrumented with digital devices and infrastructure that produce ‘big data’. Such data, smart city advocates argue enables real-time analysis of city life, new modes of urban governance, and provides the raw material for envisioning and enacting more efficient, sustainable, competitive, productive, open and transparent cities. The final section of the paper provides a critical reflection on the implications of big data and smart urbanism, examining five emerging concerns: the politics of big urban data, technocratic governance and city development, corporatisation of city governance and technological lock-ins, buggy, brittle and hackable cities, and the panoptic city.