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  • The legislative agenda in most parliamentary systems is controlled tightly by the government and bills offered by individual members of parliament have low rates of success. Yet, MPs do seek to present (private) members’ bills even where the rate of adoption is very low. We argue that members’ bills serve as an electoral connection but also as an opportunity for MPs to signal competence to their co-partisans. To demonstrate the presence of an electoral connection we take advantage of the random selection of private members’ bills in the New Zealand House of Representatives and show that survey respondents approve more of electorate MPs whose bills were drawn on the ballot. In addition, we show that MPs respond to the incentives created by the voters and parties’ willingness to reward legislative effort and, consequently, that electorally vulnerable legislators are more likely to place members’ bills on the ballot.
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    • Software/Code
    • Tabular Data
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    • Text
  • Shapefiles used in the optimization model presented in "High value of ecological information for river connectivity restoration" (Sethi et al.) In Review. Abstract: Efficient restoration of longitudinal river connectivity necessitates the use of sophisticated planning tools to maximize ecological benefits given constrained resources. Typically, ecological benefits of river barrier mitigation are measured using proxies such as the amount of accessible riverine habitat. We develop an optimization-based approach for targeting barrier mitigation which incorporates life history information of managed taxa. Findings are presented from an urbanizing salmon-bearing watershed in Alaska. Solutions informed by life history information outperformed those using only river connectivity proxies, demonstrating high value of ecological information in watershed restoration. For our study area, information on salmon ecology was typically valued at 0.8-1.2M USD based on costs savings for achieving a given benefit level relative to solutions derived with river connectivity proxies. This equated to 16-28% of the restoration budget. Investing in ecological studies may achieve win-win outcomes of improved understanding of aquatic ecology and greater watershed restoration efficiency.
    Data Types:
    • Software/Code
    • Geospatial Data
    • Document
    • File Set
  • This is the data used in the paper: Rodrigues, F. and Lourenço, M. and Ribeiro, B. and Pereira, F. C. "Learning Supervised Topic Models for Classification and Regression from Crowds". In IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017. It contains supervised learning datasets whose labels were through crowdsourcing platforms, namely Amazon Mechanical Turk, or in some cases, by simulation. These datasets cover various tasks, such as: - classifying posts and news stories; - classifying images according to their content; - predicting number of stars of a given user gave to a restaurant based on the review; - predicting movie ratings using the text of the reviews. This data is based on popular benchmark datasets: 20newsgroups, Reuters, LabelMe, we8there, MovieReviews.
    Data Types:
    • File Set
  • The following contains the data and results used in the following paper: Swati Jain, Jonathan D. Jou, Ivelin S. Georgiev, and Bruce R. Donald. A Critical Analysis of Computational Protein Design with Sparse Residue Interaction Graphs. PLoS Comp Biol. 2017, In press. Code can be found at: https://github.com/donaldlab/OSPREY_SparseAStar
    Data Types:
    • File Set
  • Normative data for the National Comprehensive Cancer Network-Functional Assessment of Cancer Therapy–Kidney Symptom Index (NFKSI). All 2000 survey respondents completed the 19-item NFKSI-19, as well as the SF-36 (Short Form 36-item instrument) and the PROMIS-29 (29-item Patient Reported Outcomes Measurement Information System), both general health status measures. Basic demographic and self-reported comorbidity data were also collected.
    Data Types:
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    • Tabular Data
  • To see how the recent financial downturn affected workers nearing retirement, the Center for Retirement Research commissioned an Internet survey of 1,317 working Americans between the ages of 45 and 59. This survey was conducted by Knowledge Networks during July and August 2009 using their nationally representative panel. A subsample of 358 individuals who had at least $50,000 in pre-downturn retirement assets and experienced a loss of at least 10%, were asked to respond to four additional questions measuring the effect of financial literacy. The survey addressed a wide range of factors that could influence workers' response to the downturn, including socio-economic, financial, employment, and behavioral characteristics.
    Data Types:
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    • Tabular Data
    • Document
    • Text
    • File Set
  • To see if attitudes are changing about the potential for using one's home to cover living expenses in retirement, the Center for Retirement Research commissioned a survey that examined the house as a potential source of retirement income. Harris Interactive® conducted the study online within the United States between January 24 and February 2, 2007 among 2,673 adults (aged 50-65). Figures for age, sex, race, education, household income, and region were weighted where necessary to bring them into line with their actual proportions in the population. Propensity score weighting was also used to adjust for respondents’ propensity to be online. The questionnaire, results, and raw data from both surveys are available.
    Data Types:
    • Other
    • Software/Code
    • Tabular Data
    • Document
    • Text
    • File Set
  • Review of Economics and Statistics: Forthcoming
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  • The zipped file contains data and programs to replicate all tables from "Lights, Camera, ... Income! Illuminating the National Accounts - Household Surveys Debate" by Maxim Pinkovskiy and Xavier Sala-i-Martin. Please see the Readme for additonal details.
    Data Types:
    • File Set
  • Updated Prefecture Points now have mostly complete spatial coverage for the Dynastic administrative units from 1350 - 1911 CE. Prefectures from earlier periods, 221 BCE to 1350 CE, still have gaps in spatial coverage.
    Data Types:
    • Image
    • File Set
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