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- Creator:
- de Oliveira, Stephanie and Nisbett, Richard E.
- Description:
- These studies assess the effect of social identity on judgement and are described in "Demographically diverse crowds are typically not much wiser than homogeneous crowds" (de Oliveira, S., & Nisbett, R. E. Proceedings of the National Academy of Sciences, 2018) and the article’s Supporting Information appendix. Some studies use a variety of questions to assess multiple social identity factors; the other studies are narrowed to particular social identity variables. Each study includes some type of estimation or prediction task, collects social identity variables, and asks participants to indicate their answer strategies. Study 1 is a trivia and prediction task based on football team fan identity. Study 2 reports on demographics plus political and religious identity and asks participants to predict vote percentages in presidential primaries. Study 3 participants estimate the percentage of Americans that support statements on various polarizing political views and give likelihood ratings for presidential candidates to win the Iowa caucus; a variety of identity questions are asked including political and religious identity. Study 4 includes demographics plus political and religious identity questions and asks participants to predict how the candidates would perform in the 2016 United States presidential election. Study 5 asks participants to guess the popularity rating of books that had either gender-specific or gender-neutral appeal, and also to rate their own interest in the books. Demographic-based social identity variables such as sex are included. Study 6 includes a wide variety of social identity variables and asks participants to estimate the likelihood of events occurring in the near future. Study 7 participants are from diverse national backgrounds and completed judgement tasks that predicted stock prices, Olympic performance, and news events outcomes. The data are generally interpretable when examined in conjunction with the target article. A new data file for Study 6 was uploaded on April 4, 2018 to include variables that were inadvertently left out of the original Study 6 file. A new data file for Study 7 was uploaded on April 6, 2018 to include variables that were inadvertently left out of the original Study 7 file. A codebook for this data set was added on April 6, 2018.
- Keyword:
- Judgment/Decision Making and Estimate aggregation
- Citation to related publication:
- Demographically diverse crowds are typically not much wiser than homogeneous crowds. Stephanie de Oliveira Richard E Nisbett Proceedings of the National Academy of Sciences of the United States of America vol. 115 issue 9 (2018) pp: 2066-2071. https://doi.org/10.1073/pnas.1717632115
- Discipline:
- Social Sciences
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- Creator:
- Geng, Yina, Van Anders, Greg, and Glotzer, Sharon C.
- Description:
- The data are the 13 target structures used in developing our model for predicting colloidal crystal structures from the geometries of particular shapes. The target structures are: simple cubic (SC), body-centered cubic (BCC), face-centered cubic (FCC), simple chiral cubic (SCC), hexagonal (HEX-1-0.6), diamond (D), graphite (G), honeycomb (H), body-centered tetragonal (BCT-1-1-2.4), high-pressure Lithium (Li), Manganese (beta-Mn), Uranium (beta-U), Tungsten (beta-W). At least nine simulations were run on each of the target structures. All of the data are formatted as .pos files.
- Keyword:
- Inverse Design and Machine Learning
- Citation to related publication:
- " Yina Geng, Greg van Anders, Sharon C. Glotzer, ""Predicting colloidal crystals from shapes via inverse design and machine learning [pre-print]"" https://arxiv.org/pdf/1801.06219.pdf"
- Discipline:
- Science
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- Creator:
- Fries, Kevin J
- Description:
- This data is in support of the publication in review "Using sensor data to dynamically map large-scale models to site-scale forecasts: A case study using the National Water Model". It is all the raw data extracted from the NWM flow forecasts for Iowa and the IFIS stage readings. For the NWM data, each date has it's own tab-delimited file with columns being the time (hrs) and rows being the NHD site. For the IFIS gages, each tab delimited file is for a single site for the period of record.
- Keyword:
- student-friendly
- Citation to related publication:
- Fries, K. J., & Kerkez, B. (2018). Using sensor data to dynamically map large-scale models to site-scale forecasts: A case study using the national water model. Water Resources Research, 54, 5636-5653. https://doi.org/10.1029/2017WR022498
- Discipline:
- Engineering
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- Creator:
- Gosner, Linda R. and Smith, Alexander J.
- Description:
- Included here are 1) a detailed description of each of the dataset's components, 2) a database of all finds from the 2015 survey, 3) a database of faunal bone compiled by specialist Damià Ramis, 4) a description of the finds by category to accompany these databases, 5) a PDF of notes taken in the field, 6) field photographs of survey units, 7) object photographs of all finds, and 8) drawings of diagnostic ceramics by time period.
- Keyword:
- Sardinia, Mediterranean archaeology, archaeological survey, pedestrian survey, and Classical archaeology
- Citation to related publication:
- Stiglitz, Alfonso, Enrique Díes Cusí, Damià Ramis, Andrea Roppa, and Peter van Dommelen. “Intorno Al Nuraghe: Notizie Preliminari Sul Progetto S’Urachi (San Vero Milis, OR).” Quaderni. Rivista Di Archeologia 26 (2015): 191–218. https://quaderniarcheocaor.beniculturali.it/index.php/qua/article/view/80/78
- Discipline:
- Social Sciences
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- Creator:
- Mathews, Elizabeth and Verhoff, Frank
- Description:
- Each pdf is an electronic version of the paper output for each experiment. Each text file is the electronic version of the data on the computer cards for each experiment. These text files are directly readable by Excel. Once in Excel, the data can be manipulated as desired. Additional information is in the theses.
- Keyword:
- Two Liquid Phase Processes, Droplet Size and Concentration, Population Balances, and Dispersed Phase Mixing
- Citation to related publication:
- Ross, S. L. (1971). Measurements and models of the dispersed phase mixing process (Doctoral dissertation). Retrieved from http://hdl.handle.net/2027.42/136886 and Verhoff, F. H. (1969). A study of the bivariate analysis of dispersed phase mixing (Doctoral dissertation). Retrieved from http://hdl.handle.net/2027.42/137651
- Discipline:
- Science and Engineering
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- Creator:
- Ridley, Aaron
- Description:
- These files (2010_gitm_input_files.tgz) were used to run GITM for 2010 for each month. GITM paper is here: (10.1016/j.jastp.2006.01.008 < http://dx.doi.org/10.1016/j.jastp.2006.01.008>) GITM code is in file gitm_170809.tgz
- Citation to related publication:
- Perlongo, N. J., Ridley, A. J., Cnossen, I., & Wu, C. (2018). A year-long comparison of GPS TEC and global ionosphere-thermosphere models. Journal of Geophysical Research: Space Physics , 123 , 1410–1428. https://doi.org/10.1002/2017JA024411
- Discipline:
- Science
-
- Creator:
- Veinot,Tiffany,C., Michigan Department of Health & Human Services, U.S. Census Bureau, American Community Survey, Data Driven Detroit, Okullo, Dolorence, and Michigan Department of Vital Statistics
- Description:
- Health status data includes data about the health of persons within a census tract in Metropolitan Detroit, measured at the census tract level. This includes data about 1) mortality by condition; 2) exposures to toxic substances; and 3) disability. Coverage for all data: 10-county Detroit-Warren-Ann Arbor Combined Statistical Area.
- Keyword:
- Community Health, Mortality Rates by Condition , Disability, Elevated Blood Lead Levels, Census Tract level, All-Cause Mortality Rates, and Spatial Measures
- Discipline:
- Health Sciences and Social Sciences
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- Creator:
- Detroit Residential Parcel Survey, United States Postal Service, Wayne County Register of Deeds, US Census, Yu, Deehan, Public and Affordable Housing Research Corporation (PAHRC), Veinot, Tiffany, RealtyTRAC, National Low Income Housing Coalition (NLIHC), Okullo, Dolorence, Wayne County Treasurer, Health Resource and Services Administration (HRSA), and Data Driven Detroit
- Description:
- This dataset includes census tract-level data concerning housing in Metropolitan Detroit. The data includes: 1) Total housing units and total mortgages in the tract; 2) Land use; 3) Real estate information (foreclosures, sales transactions, and home values); 4) Vacant housing; 5) Housing age and available facilities; 6) Housing condition; and 7) Spatial measures of subsidized housing in the tract. Data coverage should say 2006 to 2015.
- Keyword:
- Housing Conditions, Community Health, Subsidized Housing Locations, Availability of Kitchen and Plumbing Facilities, Vacant Properties, Census tract level, Age of Housing, Spatial Measures, Home Sale Transactions, Land Use by Category, Housing Units and Ownership, Housing Values, and Foreclosed Properties
- Discipline:
- Social Sciences and Health Sciences
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- Creator:
- Forrest, Stephen R., Panda, Anurag, Qu, Yue, Che, Xiaozhou, Coburn, Caleb, and Burlingame, Quinn
- Description:
- Mathematica Diffusion Simulation: Programmed by Coburn, Caleb. Simulation of diffusion in organic heterostructures, including least square fits and statistical goodness of fit analysis. Used to calculate fits to transient data in Fig 1, 3 and Extended Data Fig.2. Example data file included for download Matlab Montecarlo simulation: Programmed by Coburn, Caleb. Montecarlo simulation of charge diffusion on a cubic lattice to determine lateral diffusion length as a function of barrier height, assuming thermionic emission over the barrier. Matlab 2D Diffusion Simulation:Programmed by Coburn, Caleb. Modified from BYU Physics 430 Course Manual. Simulates diffusion around a film discontinuity, such a cut. Used to generate fits to Extended Data Fig. 1
- Keyword:
- Organic semiconductors and Charge diffusion
- Citation to related publication:
- Burlingame, Q., Coburn, C., Che, X., Panda, A., Qu, Y., & Forrest, S. R. (2018). Centimetre-scale electron diffusion in photoactive organic heterostructures. Nature, 554(7690), 77-80. https://doi.org/10.1038/nature25148
- Discipline:
- Science
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- Creator:
- Blesh, Jennifer and King, Alison E.
- Description:
- This dataset contains three data files used in: King, A.E. and J. Blesh, 2017. Crop rotations for increased soil carbon: perenniality as a guiding principle. Ecological Applications. There are also three corresponding metadata files. The file “CRMA 2017 Main.csv” contains data for the control and treatment rotations used to construct pairwise comparisons for meta-analysis, response ratios calculated for soil organic carbon concentration, and change in carbon input. The dataset also includes management, soil, and other environmental characteristics for each site. The file “CRMA 2017 Diversity x Nitrogen.csv” contains data used to test whether N fertilizer inputs mediated the effect of functional diversity on SOC concentrations. The file “CRMA Annual grain.csv” contains data used to test for effects of crop rotation species diversity (one vs. two species, or two vs. three species) on SOC concentrations and C input (i.e., for the “grain-only” rotations). The dataset also includes management, soil, and other environmental characteristics for each site. The corresponding metadata files: “CRMA 2017 Main_metadata.csv”, “CRMA 2017 Diversity x Nitrogen_metadata.csv”, and “CRMA Annual grain _metadata.csv” provide a detailed description of all variables in each dataset. Note: On Jan 12, 2018 the following information was added to the three metadata files: the name of the data file the metadata refers to, an explanation as to the meaning of blank cells in the data file, a full citation to the paper where the author describes her findings and contact information for the author.
- Keyword:
- soil carbon, functional diversity, meta-analysis, cropping system, and student-friendly
- Citation to related publication:
- King, A. E. and Blesh, J. (2018), Crop rotations for increased soil carbon: perenniality as a guiding principle. Ecol Appl, 28: 249–261. https://doi.org/10.1002/eap.1648
- Discipline:
- Science