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See README.pdf
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The 2004 General Social Survey (GSS) reported significant increases in social isolation and significant decreases in ego network size relative to previous periods. These results have been repeatedly challenged. Critics have argued that malfeasant interviewers, coding errors, or training effects lie behind these results. While each critique has some merit, none precisely identify the cause of decreased ego network size. In this article, we show that it matters that the 2004 GSS—unlike other GSS surveys—was fielded during a highly polarized election period. We find that the difference in network size between nonpartisan and partisan voters in the 2004 GSS is larger than in all other GSS surveys. We further discover that core discussion network size decreases precipitously in the period immediately around the first (2004) presidential debate, suggesting that the debate frames “important matters” as political matters. This political priming effect is stronger where geographic polarization is weaker and among those who are politically interested and talk about politics more often. Combined, these findings identify the specific mechanism for the reported decline in network size, indicate that inferences about increased social isolation in America arising from the 2004 GSS are unwarranted, and suggest the emergence of increased political isolation.
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Official election results for quadrennial Presidential elections, arranged by type of election and year.
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Replication dataset and script
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We parameteraized and validated the Soil Water Assessment Tool (SWAT) for major watersheds feeding the coastal wetlands. According to the downscaled GCM outputs for the next 50 years, we simulated the water discharges from the watersheds of Rio Grande de Loiza and Rio Culebrinas in 2011 - 2060.
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Experts predict that the climate change will affect all natural and human systems. Historical climate records show changes in average and extreme temperatures, as well as an increase in annual climate variability; this changes can affect all continents of our planet in different ways and the high levels of poverty in some regions can worsen the impacts of climate change. In addition, families who are dedicated to making agriculture and owning small land units directly dependent on its production to keep your family economy. The purpose of this research was to identify levels of vulnerability of coffee farming families in four countries of the Mesoamerican Region (Nicaragua, Guatemala, El Salvador and Mexico), because coffee is an important livelihood for thousands of families in this region. In order to know the response of crops to projected changes, the state of their resources and ultimately the strategies that they can implement to minimize the impact of climate change, this research was done using climate models to project the coffee climate suitability and the exposure in this regions; also qualitative tools were combined under the focus on livelihoods and resources of families to identify the vulnerability level.
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Data products to support reproduction of the first interferometric localization of Fast Radio Burst 121102. First publication available at http://dx.doi.org/10.1038/nature20797 and data analysis recipes are available at http://github.com/caseyjlaw/FRB121102. The principle data products are nine tar files of fast-sampled interferometric data from the Very Large Array. Each observation segment includes 4 seconds (800 integrations) of visibilities centered on a radio burst from FRB 121102. Data is in science data model (SDM) format, which consists of a directory with metadata in XML files and binary data in the ASDMBinary subdirectory. Binary data were recorded with an integration time of 5 ms, frequencies at S-band (2.5-3.5 GHz; 256 channels), and dual-circular polarizations. Each file is identified by a unique name of the observation, plus the observation start time in MJD. Each visibility data set has an associated calibration file (telcal format; ending in ".GN") that can be parsed to apply gain calibration. The Python package rtpipe (https://github.com/caseyjlaw/rtpipe) can perform all calibration and analysis of these data. This library is supported by sdmpy (https://github.com/demorest/sdmpy), a Python library to read SDM files, and pwkit (https://github.com/pkgw/pwkit), a Python interface to the CASA data analysis package. See also http://realfast.io for information on the project behind the data acquisition system and analysis software.
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Replication code and sample data used for above mentioned publication in Political Analysis.
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Additional Data for the publication "Absolute Configuration of Native Oligomeric Proanthocyanidins with Dentin Biomodification Potency" in the Journal of Organic Chemistry
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Prior scholarship overlooks the capacity of other actors to raise the political costs of unilateral action by turning public opinion against the president. Through a series of five experiments embedded on nationally representative surveys, we demonstrate Congress’ ability to erode support for unilateral actions by raising both constitutional and policy-based objections to the exercise of unilateral power. Congressional challenges to the unilateral president diminish support for executive action across a range of policy areas in both the foreign and domestic realm and are particularly influential when they explicitly argue that presidents are treading on congressional prerogatives. We also find evidence that constitutional challenges are more effective when levied by members of Congress than by other actors. The results resolve a debate in the literature and suggest a mechanism through which Congress might exercise a constraint on the president, even when it is unable to check him legislatively.
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