- Aug 2020
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www.thelancet.com www.thelancet.com
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Kc, A., Gurung, R., Kinney, M. V., Sunny, A. K., Moinuddin, M., Basnet, O., Paudel, P., Bhattarai, P., Subedi, K., Shrestha, M. P., Lawn, J. E., & Målqvist, M. (2020). Effect of the COVID-19 pandemic response on intrapartum care, stillbirth, and neonatal mortality outcomes in Nepal: A prospective observational study. The Lancet Global Health, 0(0). https://doi.org/10.1016/S2214-109X(20)30345-4
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CNN, C. M. (n.d.). Previous vaccines and masks may hold down Covid-19, some researchers say. CNN. Retrieved 12 August 2020, from https://www.cnn.com/2020/08/11/health/us-coronavirus-tuesday/index.html
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AP NEWS. ‘Health Officials Are Quitting or Getting Fired amid Outbreak’, 10 August 2020. https://apnews.com/8ea3b3669bccf8a637b81f8261f1cd78.
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www.nber.org www.nber.org
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Harris, J. E. (2020). Reopening Under COVID-19: What to Watch For (Working Paper No. 27166; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27166
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covid-19.iza.org covid-19.iza.org
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Bertoli, S., Guichard, L., & Marchetta, F. (2020). Turnout in the Municipal Elections of March 2020 and Excess Mortality during the COVID-19 Epidemic in France. IZA Discussion Paper, 13335.
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Cajner, T., Crane, L. D., Decker, R. A., Grigsby, J., Hamins-Puertolas, A., Hurst, E., Kurz, C., & Yildirmaz, A. (2020). The U.S. Labor Market during the Beginning of the Pandemic Recession (Working Paper No. 27159; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27159
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Gale, W. G., Gelfond, H., Fichtner, J. J., & Harris, B. H. (2020). The Wealth of Generations, With Special Attention to the Millennials (Working Paper No. 27123; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27123
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Peterson, David, and Aaron Panofsky. ‘Metascience as a Scientific Social Movement’. Preprint. SocArXiv, 4 August 2020. https://doi.org/10.31235/osf.io/4dsqa.
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www.nber.org www.nber.org
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Hansman, C., Hong, H., de Paula, Á., & Singh, V. (2020). A Sticky-Price View of Hoarding (Working Paper No. 27051; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27051
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www.nber.org www.nber.org
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Aizenman, Joshua, Yothin Jinjarak, Donghyun Park, and Huanhuan Zheng. ‘Good-Bye Original Sin, Hello Risk On-Off, Financial Fragility, and Crises?’ National Bureau of Economic Research Working Paper Series, 23 April 2020. https://www.nber.org/papers/w27030.
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Stock, James H. ‘Data Gaps and the Policy Response to the Novel Coronavirus’. Working Paper. Working Paper Series. National Bureau of Economic Research, March 2020. https://doi.org/10.3386/w26902.
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en.wikipedia.org en.wikipedia.org
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In graph theory, a tree is a connected acyclic graph; unless stated otherwise, in graph theory trees and graphs are assumed undirected. There is no one-to-one correspondence between such trees and trees as data structure.
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www.nber.org www.nber.org
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Correa, R., Du, W., & Liao, G. Y. (2020). U.S. Banks and Global Liquidity (Working Paper No. 27491; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27491
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www.nber.org www.nber.org
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Alstadsæter, A., Bratsberg, B., Eielsen, G., Kopczuk, W., Markussen, S., Raaum, O., & Røed, K. (2020). The First Weeks of the Coronavirus Crisis: Who Got Hit, When and Why? Evidence from Norway (Working Paper No. 27131; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27131
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Annotators
URL
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www.nber.org www.nber.org
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Hong, H., Wang, N., & Yang, J. (2020). Implications of Stochastic Transmission Rates for Managing Pandemic Risks (Working Paper No. 27218; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27218
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www.nber.org www.nber.org
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Nguyen, T. D., Gupta, S., Andersen, M., Bento, A., Simon, K. I., & Wing, C. (2020). Impacts of State Reopening Policy on Human Mobility (Working Paper No. 27235; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27235
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www.nber.org www.nber.org
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Baker, S. R., Farrokhnia, R. A., Meyer, S., Pagel, M., & Yannelis, C. (2020). How Does Household Spending Respond to an Epidemic? Consumption During the 2020 COVID-19 Pandemic (Working Paper No. 26949; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w26949
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www.nber.org www.nber.org
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Kahn, L. B., Lange, F., & Wiczer, D. G. (2020). Labor Demand in the Time of COVID-19: Evidence from Vacancy Postings and UI Claims (Working Paper No. 27061; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27061
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www.nber.org www.nber.org
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Goolsbee, A., & Syverson, C. (2020). Fear, Lockdown, and Diversion: Comparing Drivers of Pandemic Economic Decline 2020 (Working Paper No. 27432; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27432
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Manski, C. F., & Molinari, F. (2020). Estimating the COVID-19 Infection Rate: Anatomy of an Inference Problem (Working Paper No. 27023; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27023
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onlinelibrary.wiley.com onlinelibrary.wiley.com
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Collins, G. S., & Wilkinson, J. (n.d.). Statistical issues in the development a COVID-19 prediction models. Journal of Medical Virology, n/a(n/a). https://doi.org/10.1002/jmv.26390
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covid-19.iza.org covid-19.iza.org
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Germany’s Capacities to Work from Home. COVID-19 and the Labor Market. (n.d.). IZA – Institute of Labor Economics. Retrieved August 8, 2020, from https://covid-19.iza.org/publications/dp13152/
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covid-19.iza.org covid-19.iza.org
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Who Can Work from Home?. COVID-19 and the Labor Market. (n.d.). IZA – Institute of Labor Economics. Retrieved August 7, 2020, from https://covid-19.iza.org/publications/dp13197/
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Barrios, J. M., Benmelech, E., Hochberg, Y. V., Sapienza, P., & Zingales, L. (2020). Civic Capital and Social Distancing during the Covid-19 Pandemic (Working Paper No. 27320; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27320
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www.nber.org www.nber.org
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Brynjolfsson, E., Horton, J. J., Ozimek, A., Rock, D., Sharma, G., & TuYe, H.-Y. (2020). COVID-19 and Remote Work: An Early Look at US Data (Working Paper No. 27344; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27344
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covid-19.iza.org covid-19.iza.org
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Modelling the Distributional Impact of the COVID-19 Crisis. COVID-19 and the Labor Market. (n.d.). IZA – Institute of Labor Economics. Retrieved August 5, 2020, from https://covid-19.iza.org/publications/dp13235/
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covid-19.iza.org covid-19.iza.org
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On the Effects of COVID-19 Safer-At-Home Policies on Social Distancing, Car Crashes and Pollution. (n.d.). IZA – Institute of Labor Economics. Retrieved August 4, 2020, from https://covid-19.iza.org/publications/dp13255/
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covid-19.iza.org covid-19.iza.org
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Six-Country Survey on COVID-19 (n.d.). IZA – Institute of Labor Economics. Retrieved August 4, 2020, from https://covid-19.iza.org/publications/dp13230/
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covid-19.iza.org covid-19.iza.org
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Lockdown Accounting. COVID-19 and the Labor Market. (n.d.). IZA – Institute of Labor Economics. Retrieved August 1, 2020, from https://covid-19.iza.org/publications/dp13397/
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covid-19.iza.org covid-19.iza.org
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Public Attention and Policy Responses to COVID-19 Pandemic. COVID-19 and the Labor Market. (n.d.). IZA – Institute of Labor Economics. Retrieved July 31, 2020, from https://covid-19.iza.org/publications/dp13427/
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covid-19.iza.org covid-19.iza.org
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Urban Density and COVID-19. COVID-19 and the Labor Market. (n.d.). IZA – Institute of Labor Economics. Retrieved July 30, 2020, from https://covid-19.iza.org/publications/dp13440/
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covid-19.iza.org covid-19.iza.org
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EU Jobs at Highest Risk of COVID-19 Social Distancing: Will the Pandemic Exacerbate Labour Market Divide?. COVID-19 and the Labor Market. (n.d.). IZA – Institute of Labor Economics. Retrieved July 29, 2020, from https://covid-19.iza.org/publications/dp13281/
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covid-19.iza.org covid-19.iza.org
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Lockdown Strategies, Mobility Patterns and COVID-19. COVID-19 and the Labor Market. (n.d.). IZA – Institute of Labor Economics. Retrieved July 29, 2020, from https://covid-19.iza.org/publications/dp13293/
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covid-19.iza.org covid-19.iza.org
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Does the COVID-19 Pandemic Improve Global Air Quality? New Cross-National Evidence on Its Unintended Consequences. COVID-19 and the Labor Market. (n.d.). IZA – Institute of Labor Economics. Retrieved July 29, 2020, from https://covid-19.iza.org/publications/dp13480/
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covid-19.iza.org covid-19.iza.org
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Intergenerational Residence Patterns and COVID-19 Fatalities in the EU and the US. COVID-19 and the Labor Market. (n.d.). IZA – Institute of Labor Economics. Retrieved July 29, 2020, from https://covid-19.iza.org/publications/dp13452/
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covid-19.iza.org covid-19.iza.org
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Exploring the Relationship between Care Homes and Excess Deaths in the COVID-19 Pandemic: Evidence from Italy. COVID-19 and the Labor Market. (n.d.). IZA – Institute of Labor Economics. Retrieved July 27, 2020, from https://covid-19.iza.org/publications/dp13492/
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covid-19.iza.org covid-19.iza.org
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Reacting Quickly and Protecting Jobs: The Short-Term Impacts of the COVID-19 Lockdown on the Greek Labor Market. COVID-19 and the Labor Market. (n.d.). IZA – Institute of Labor Economics. Retrieved July 27, 2020, from https://covid-19.iza.org/publications/dp13516/
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stackoverflow.blog stackoverflow.blog
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Valhalla aims to revise the memory model for Java to allow for immutable types, which are more complex than primitives, but less flexible than objects. Sometimes you have more complex data that doesn’t change over the course of that object’s lifespan; burdening it with the overhead of a class is unnecessary. The initial proposal put it more succinctly: “Codes like a class, works like an int.” “For things like big data for machine learning or for natural language, Valhalla promises to represent data in a way that allows the JVM to fully take advantage of modern hardware architectures that have changed dramatically since Java was created,” said Saab.
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psyarxiv.com psyarxiv.com
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Webster, G. D., Howell, J. L., Losee, J. E., Mahar, E., & Wongsomboon, V. (2020). Culture, COVID-19, and Collectivism: A Paradox of American Exceptionalism? [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/hqcs6
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journals.plos.org journals.plos.org
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Aleta, A., Arruda, G. F. de, & Moreno, Y. (2020). Data-driven contact structures: From homogeneous mixing to multilayer networks. PLOS Computational Biology, 16(7), e1008035. https://doi.org/10.1371/journal.pcbi.1008035
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www.youtube.com www.youtube.com
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MyData vs. COVID-19 calls (2020, June 5) - https://www.youtube.com/playlist?list=PLbpRS19STpXSWs4kTiVEx2KN5CZh6yCYI
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Brown, C. S., Ravallion, M., & van de Walle, D. (2020). Can the World’s Poor Protect Themselves from the New Coronavirus? (Working Paper No. 27200; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27200
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www.nber.org www.nber.org
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Baqaee, D., Farhi, E., Mina, M. J., & Stock, J. H. (2020). Reopening Scenarios (Working Paper No. 27244; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27244
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public.tableau.com public.tableau.com
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Roll over each school to find out more information on their respective plans. (n.d.). Tableau Software. Retrieved August 2, 2020, from https://public.tableau.com/views/NESCACFallPlansMap/Dashboard1
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osr.statisticsauthority.gov.uk osr.statisticsauthority.gov.uk
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COVID-19 Local Area Data. (n.d.). Office for Statistics Regulation. Retrieved August 2, 2020, from https://osr.statisticsauthority.gov.uk/news/covid-19-local-area-data/
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www.nber.org www.nber.org
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Monte, F. (2020). Mobility Zones (Working Paper No. 27236; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27236
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- Jul 2020
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www.ons.gov.uk www.ons.gov.uk
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Deaths registered weekly in England and Wales, provisional—Office for National Statistics. (n.d.). Retrieved 31 July 2020, from https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/bulletins/deathsregisteredweeklyinenglandandwalesprovisional/weekending17july2020
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covid-19.iza.org covid-19.iza.org
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COVID-19 and the Labor Market. (n.d.). IZA – Institute of Labor Economics. Retrieved 31 July 2020, from https://covid-19.iza.org/publications/dp13388/
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www.nber.org www.nber.org
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Dave, D. M., Friedson, A. I., Matsuzawa, K., McNichols, D., Redpath, C., & Sabia, J. J. (2020). Did President Trump’s Tulsa Rally Reignite COVID-19? Indoor Events and Offsetting Community Effects (Working Paper No. 27522; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27522
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www.nber.org www.nber.org
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Friedson, A. I., McNichols, D., Sabia, J. J., & Dave, D. (2020). Did California’s Shelter-in-Place Order Work? Early Coronavirus-Related Public Health Effects (Working Paper No. 26992; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w26992
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www.nber.org www.nber.org
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Cotti, C. D., Engelhardt, B., Foster, J., Nesson, E. T., & Niekamp, P. S. (2020). The Relationship between In-Person Voting and COVID-19: Evidence from the Wisconsin Primary (Working Paper No. 27187; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27187
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www.nber.org www.nber.org
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Aucejo, E. M., French, J. F., Araya, M. P. U., & Zafar, B. (2020). The Impact of COVID-19 on Student Experiences and Expectations: Evidence from a Survey (Working Paper No. 27392; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27392
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www.nber.org www.nber.org
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Chang, H.-H., & Meyerhoefer, C. (2020). COVID-19 and the Demand for Online Food Shopping Services: Empirical Evidence from Taiwan (Working Paper No. 27427; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27427
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www.nber.org www.nber.org
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Dave, D. M., Friedson, A. I., Matsuzawa, K., & Sabia, J. J. (2020). When Do Shelter-in-Place Orders Fight COVID-19 Best? Policy Heterogeneity Across States and Adoption Time (Working Paper No. 27091; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27091
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Papanikolaou, D., & Schmidt, L. D. W. (2020). Working Remotely and the Supply-side Impact of Covid-19 (Working Paper No. 27330; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27330
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www.nber.org www.nber.org
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Schmitt-Grohé, S., Teoh, K., & Uribe, M. (2020). Covid-19: Testing Inequality in New York City (Working Paper No. 27019; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27019
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epjdatascience.springeropen.com epjdatascience.springeropen.com
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Fatehkia, M., Tingzon, I., Orden, A., Sy, S., Sekara, V., Garcia-Herranz, M., & Weber, I. (2020). Mapping socioeconomic indicators using social media advertising data. EPJ Data Science, 9(1), 1–15. https://doi.org/10.1140/epjds/s13688-020-00235-w
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walker-data.com walker-data.com
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Working with Census microdata. (n.d.). Retrieved July 31, 2020, from https://walker-data.com/tidycensus/articles/pums-data.html
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Coronavirus (COVID-19): Daily data for Scotland—Gov.scot. (n.d.). Retrieved July 31, 2020, from https://www.gov.scot/publications/coronavirus-covid-19-daily-data-for-scotland/
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github.com github.com
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Ruby has some really nice libraries for working with linked data. These libraries allow you to work with the data in both a graph and resource-oriented fashion, allowing a developer to use the techniques that best suit his or her use cases and skills.
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Another Ruby gem, Spira, allows graph data to be used as model objects
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www.w3.org www.w3.org
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As a result, web browsers can provide only minimal assistance to humans in parsing and processing web pages: browsers only see presentation information.
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json-ld.org json-ld.org
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amp.dev amp.dev
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To verify that your structured data is correct, many platforms provide validation tools. In this tutorial, we'll validate our structured data with the Google Structured Data Validation Tool.
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Valid AMP pages do not require schema.org structured data, but some platforms like Google Search require it for certain experiences like the Top stories carousel. It's generally a good idea to include structured data. Structured data helps search engines to better understand your web page, and to better display your content in Search Engine Result Pages (e.g., in rich snippets).
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edpb.europa.eu edpb.europa.eu
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As mentioned earlier in these guidelines, it is very important that controllers assess the purposes forwhich data is actually processed and the lawful grounds on which it is based prior to collecting thedata. Often companies need personal data for several purposes, and the processing is based on morethan one lawful basis, e.g. customer data may be based on contract and consent. Hence, a withdrawalof consent does not mean a controller must erase data that are processed for a purpose that is basedon the performance of the contract with the data subject. Controllers should therefore be clear fromthe outset about which purpose applies to each element of data and which lawful basis is being reliedupon.
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If there is no other lawful basisjustifying the processing (e.g. further storage) of the data, they should be deleted by the controller.
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In cases where the data subject withdraws his/her consent and the controller wishes to continue toprocess the personal data on another lawful basis, they cannot silently migrate from consent (which iswithdrawn) to this other lawful basis. Any change in the lawful basis for processing must be notified toa data subject in accordance with the information requirements in Articles 13 and 14 and under thegeneral principle of transparency.
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Data minimization, anonymisation and datasecurity are mentioned as possible safeguards.73Anonymisation is the preferred solution as soon asthe purpose of the research can be achieved without the processing of personal data.
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www.iubenda.com www.iubenda.com
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Some vendors may relay on legitimate interest instead of consent for the processing of personal data. The User Interface specifies if a specific vendor is relating on legitimate interest as legal basis, meaning that that vendor will process user’s data for the declared purposes without asking for their consent. The presence of vendors relying on legitimate interest is the reason why within the user interface, even if a user has switched on one specific purpose, not all vendors processing data for that purpose will be displayed as switched on. In fact, those vendors processing data for that specific purpose, relying only on legitimate interest will be displayed as switched off.
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Under GDPR there are six possible legal bases for the processing of personal data.
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addons.mozilla.org addons.mozilla.org
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easy access/edit/backup and then restore saved data using the integrated Bookmark Manager (even on smartphone / tablet) even if the addon is not installed
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Why save sessions as bookmarks? - all the data saved will be there no matter what addon you may use in the feature
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www.nber.org www.nber.org
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Fernández-Villaverde, J., & Jones, C. I. (2020). Estimating and Simulating a SIRD Model of COVID-19 for Many Countries, States, and Cities (Working Paper No. 27128; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27128
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www.nber.org www.nber.org
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www.nber.org www.nber.org
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Granja, J., Makridis, C., Yannelis, C., & Zwick, E. (2020). Did the Paycheck Protection Program Hit the Target? (Working Paper No. 27095; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27095
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sites.google.com sites.google.com
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drawing evidence-based conclusions
One thing that is not obvious about Hypothesis, is that you can also use it to annotate data sheets — that's easiest if they are CSV files published on the web.
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psyarxiv.com psyarxiv.com
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Litman. L,. Hartman. R., Jaffe. S., Robinson. J. (2020) County-level recruitment in online samples: Applications to COVID-19 and beyond. PsyArXiv Preprints. Retrieved from: https://psyarxiv.com/g3xw7/
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www.youtube.com www.youtube.com
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MCLS Virtual Brown Bag June 12, 2020: Bayesian Modelling. (2020, June 15). https://www.youtube.com/watch?v=7LLZPNLhn5o
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Follow the money: See where $380B in Paycheck Protection Program money went. (n.d.). Retrieved July 27, 2020, from https://www.cnn.com/projects/ppp-business-loans/
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Do jeszcze bardziej przytłaczających wniosków doszła Julianne Holt-Lunstad, która, posiłkując się wynikami 70 badań naukowych, ogłosiła, że samotność zwiększa śmiertelność w takim samym stopniu co otyłość czy wypalanie 15 papierosów dziennie. Z kolei Nicole Valtorty z Uniwersytetu Newcastle ustaliła, że prawdopodobieństwo ataku serca u osób osamotnionych rośnie o 29 proc., a zagrożenie udarem – o 32 proc. „To niezależny czynnik przyczyniający się do śmierci. Może cię po prostu zabić. Znajduje się na tej samej liście co choroby serca i rak – twierdzi dr Josh Klapow, psycholog kliniczny z Uniwersytetu Alabamy.
Data on health consequences of being alone
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Z danych GUS-u i tych zebranych przez portale randkowe wynika, że w Polsce w ciągu ostatnich 10 lat liczba osób żyjących samotnie wzrosła o 34 proc.
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Wśród krajów europejskich w niechlubnym rankingu zwycięża jednak Szwecja, w stolicy której samotnie mieszka aż 58 proc.(!) populacji. Z kolei w Stanach Zjednoczonych odsetek ten wynosi 27 proc. (w Nowym Jorku prawie 50 proc.) i cały czas rośnie – dla porównania w roku 1920 jednoosobowe gospodarstwo domowe prowadziło tam 5 proc. obywateli.
Percentage of people living alone
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Luscombe, A., & McClelland, A. (2020). Policing the Pandemic: Tracking the Policing of Covid-19 across Canada [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/9pn27
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osf.io osf.io
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La, V.-P., Pham, T.-H., Ho, T. M., Hoàng, N. M., Linh, N. P. K., Vuong, T.-T., Nguyen, H.-K. T., Tran, T., Van Quy, K., Ho, T. M., & Vuong, Q.-H. (2020). Policy response, social media and science journalism for the sustainability of the public health system amid the COVID-19 outbreak: The Vietnam lessons [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/cfw8x
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osf.io osf.io
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Motta, M., Stecula, D., & Farhart, C. E. (2020). How Right-Leaning Media Coverage of COVID-19 Facilitated the Spread of Misinformation in the Early Stages of the Pandemic [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/a8r3p
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akkshaya.blog akkshaya.blog
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the market size: the global note-taking management software market is estimated to reach $1.35 billion by 2026, growing at a CAGR of 5.32% from 2019 to 2026greater scope for innovation: eg., be it creating a task list, a roadmap, or a design repository, Notion can handle it alllack of satisfaction: it’s noted that people always use a combination of note-taking apps and hardly stick to one for a long time
Three reasons why we constantly see more note-taking apps, which in return increase our paradox of choice
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osf.io osf.io
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Kubinec, R., & Carvalho, L. (2020). A Retrospective Bayesian Model for Measuring Covariate Effects on Observed COVID-19 Test and Case Counts [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/jp4wk
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science.sciencemag.org science.sciencemag.org
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Barton, C. M., Alberti, M., Ames, D., Atkinson, J.-A., Bales, J., Burke, E., Chen, M., Diallo, S. Y., Earn, D. J. D., Fath, B., Feng, Z., Gibbons, C., Hammond, R., Heffernan, J., Houser, H., Hovmand, P. S., Kopainsky, B., Mabry, P. L., Mair, C., … Tucker, G. (2020). Call for transparency of COVID-19 models. Science, 368(6490), 482.2-483. https://doi.org/10.1126/science.abb8637
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docs.google.com docs.google.com
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COVID-19 Social Science Tracker - Google Sheets
Tags
- tracker
- conspiracy theory
- research
- behavior
- isolation
- preprint
- social media
- lang:en
- COVID-19
- analysis
- social distancing
- uncertainty
- international
- community
- spreadsheet
- medicine
- mental health
- is:other
- misinformation
- government
- policy
- sheets
- unofficial
- data collection
- social norm
- healthcare
- publication
- infection
- social science
Annotators
URL
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van Rooij, B., de Bruijn, A. L., Reinders Folmer, C., Kooistra, E., Kuiper, M. E., Brownlee, M., … Fine, A. (2020, April 22). Compliance with COVID-19 Mitigation Measures in the United States. https://doi.org/10.31234/osf.io/qymu3
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Betsch, C. How behavioural science data helps mitigate the COVID-19 crisis. Nat Hum Behav (2020). https://doi.org/10.1038/s41562-020-0866-1
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www.thelancet.com www.thelancet.com
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The Lancet. (2020). The gendered dimensions of COVID-19. The Lancet, 395(10231), 1168. https://doi.org/10.1016/S0140-6736(20)30823-0
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Perrott, D. (2020, May 26). Is Applied Behavioural Science reaching a Local Maximum? Medium. https://medium.com/@DavePerrott/is-applied-behavioural-science-reaching-a-local-maximum-538b536f7e7d
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osf.io osf.io
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Goldman, D. S. (2020). Initial Observations of Psychological and Behavioral Effects of COVID-19 in the United States, Using Google Trends Data. https://doi.org/10.31235/osf.io/jecqp
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osf.io osf.io
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Bernardi, F., Cozzani, M., & Zanasi, F. (2020). Social inequality and the risk of being in a nursing home during the COVID-19 pandemic [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/ksefy
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Metternich, N. W. (2020). Drawback before the wave?: Protest decline during the Covid-19 pandemic. https://doi.org/10.31235/osf.io/3ej72
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www.sg.uu.nl www.sg.uu.nl
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Dr. Maarten van Smeden (2020, May 11). Understanding the statistics of the coronavirus. Universiteit Utrecht. https://www.sg.uu.nl/video/2020/06/understanding-statistics-coronavirus
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www.youtube.com www.youtube.com
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Data Intersections 2020 | Heather Krause. (2020, February 21). How not to use data like a racist. https://www.youtube.com/watch?v=EGO7yevPHDk
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osf.io osf.io
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Payne, J. L., & Morgan, A. (2020). COVID-19 and Violent Crime: A comparison of recorded offence rates and dynamic forecasts (ARIMA) for March 2020 in Queensland, Australia [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/g4kh7
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osf.io osf.io
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Rice, W. L., Mateer, T., Taff, B. D., Lawhon, B., Reigner, N., & Newman, P. (2020). The COVID-19 pandemic continues to change the way people recreate outdoors: A second preliminary report on a national survey of outdoor enthusiasts amid the COVID-19 pandemic. https://doi.org/10.31235/osf.io/dghba
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osf.io osf.io
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Payne, J. L., & Morgan, A. (2020). Property Crime during the COVID-19 Pandemic: A comparison of recorded offence rates and dynamic forecasts (ARIMA) for March 2020 in Queensland, Australia [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/de9nc
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osf.io osf.io
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Stephany, F., Dunn, M., Sawyer, S., & Lehdonvirta, V. (2020). Distancing Bonus or Downscaling Loss? The Changing Livelihood of US Online Workers in Times of COVID-19 [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/vmg34
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osf.io osf.io
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Dudel, C., Riffe, T., Acosta, E., van Raalte, A. A., Strozza, C., & Myrskylä, M. (2020). Monitoring trends and differences in COVID-19 case fatality rates using decomposition methods: Contributions of age structure and age-specific fatality [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/j4a3d
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osf.io osf.io
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Arpino, B., Bordone, V., & Pasqualini, M. (2020). Are intergenerational relationships responsible for more COVID-19 cases? A cautionary tale of available empirical evidence [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/y8hpr
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www.youtube.com www.youtube.com
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American Philosophical Society. (2020, June 08). Evidence Symposium. YouTube. https://www.youtube.com/playlist?list=PLoKwLGnyZL4Ds5cQo5muFMg8zKXK4KobH
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wellcomeopenresearch.org wellcomeopenresearch.org
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Jeffrey, B., Walters, C. E., Ainslie, K. E. C., Eales, O., Ciavarella, C., Bhatia, S., Hayes, S., Baguelin, M., Boonyasiri, A., Brazeau, N. F., Cuomo-Dannenburg, G., FitzJohn, R. G., Gaythorpe, K., Green, W., Imai, N., Mellan, T. A., Mishra, S., Nouvellet, P., Unwin, H. J. T., … Riley, S. (2020). Anonymised and aggregated crowd level mobility data from mobile phones suggests that initial compliance with COVID-19 social distancing interventions was high and geographically consistent across the UK. Wellcome Open Research, 5, 170. https://doi.org/10.12688/wellcomeopenres.15997.1
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Gleeson, J. P., Onaga, T., Fennell, P., Cotter, J., Burke, R., & O’Sullivan, D. J. P. (2020). Branching process descriptions of information cascades on Twitter. ArXiv:2007.08916 [Physics]. http://arxiv.org/abs/2007.08916
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Jul 2, N. H. / P. (2020, July 2). Urban density not linked to higher coronavirus infection rates. The Hub. https://hub.jhu.edu/2020/07/02/urban-density-not-linked-to-higher-covid-19-infection-rates/
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www.medrxiv.org www.medrxiv.org
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Fonseca, S. C., Rivas, I., Romaguera, D., Quijal-Zamorano, M., Czarlewski, W., Vidal, A., Fonseca, J. A., Ballester, J., Anto, J. M., Basagana, X., Cunha, L. M., & Bousquet, J. (2020). Association between consumption of vegetables and COVID-19 mortality at a country level in Europe. MedRxiv, 2020.07.17.20155846. https://doi.org/10.1101/2020.07.17.20155846
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www.opentable.com www.opentable.com
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OpenTable. ‘State of the Industry’. Accessed 20 July 2020. https://www.opentable.com/state-of-industry.
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jamanetwork.com jamanetwork.com
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Weinberger, D. M., Chen, J., Cohen, T., Crawford, F. W., Mostashari, F., Olson, D., Pitzer, V. E., Reich, N. G., Russi, M., Simonsen, L., Watkins, A., & Viboud, C. (2020). Estimation of Excess Deaths Associated With the COVID-19 Pandemic in the United States, March to May 2020. JAMA Internal Medicine. https://doi.org/10.1001/jamainternmed.2020.3391
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twitter.com twitter.com
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Maarten van Smeden on Twitter: “This is a kind reminder that most issues with data (e.g. measurement error, incomplete data, confounding, selection) do not disappear just because you have N = ginormous” / Twitter. (n.d.). Twitter. Retrieved July 19, 2020, from https://twitter.com/MaartenvSmeden/status/1283313496382373890
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www.nationalgeographic.com www.nationalgeographic.com
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How scientists know COVID-19 is way deadlier than the flu. (2020, July 2). Science. https://www.nationalgeographic.com/science/2020/07/coronavirus-deadlier-than-many-believed-infection-fatality-rate-cvd/
Tags
- is:news
- lethality
- epidemiology
- research
- clarity
- transmission
- lang:en
- COVID-19
- concern
- potency
- case increase
- science
- data analysis
- USA
- potential
Annotators
URL
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www.nationalgeographic.com www.nationalgeographic.com
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Coronavirus News and Coverage. (n.d.). Science. Retrieved July 18, 2020, from https://www.nationalgeographic.com/science/coronavirus-coverage/
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innovationinpolitics.eu innovationinpolitics.eu
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Coping with the Crisis | Introduction. (n.d.). The Innovation in Politics Institute. Retrieved July 18, 2020, from https://innovationinpolitics.eu/en/coping-with-the-coronavirus-crisis/introduction/
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twitter.com twitter.com
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Ed Conway on Twitter: “Breaking: UK government was routinely overstating the total number of people who’d been tested for #COVID19 by as many as 200,000 at the height of the coronavirus pandemic, according to new Sky News analysis.” / Twitter. (n.d.). Twitter. Retrieved July 17, 2020, from https://twitter.com/EdConwaySky/status/1281652670000844800
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www.gov.uk www.gov.uk
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Number of people tested for coronavirus (England): 30 January to 27 May 2020. (n.d.). GOV.UK. Retrieved July 17, 2020, from https://www.gov.uk/government/publications/number-of-people-tested-for-coronavirus-england-30-january-to-27-may-2020
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osf.io osf.io
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Kulu, H., & Dorey, P. (2020). Infection Rates from Covid-19 in Great Britain by Geographical Units: A Model-based Estimation from Mortality Data [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/84f3e
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osf.io osf.io
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Haman, M. (2020). The use of Twitter by state leaders and its impact on the public during the COVID-19 pandemic. https://doi.org/10.31235/osf.io/u4maf
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twitter.com twitter.com
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ReconfigBehSci on Twitter: ‘RT @ObsoleteDogma: The U.S. is averaging more new covid cases than any continent is right now https://t.co/O70nj0I4Xo’ / Twitter. (n.d.). Twitter. Retrieved 16 July 2020, from https://twitter.com/SciBeh/status/1282953988774727680
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osf.io osf.io
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Graham, A., Cullen, F. T., Pickett, J., Jonson, C. L., Haner, M., & Sloan, M. M. (2020). Faith in Trump, Moral Foundations, and Social Distancing Defiance During the Coronavirus Pandemic [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/fudzq
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Fitzgerald, R. M. (2020). WAKING TO NORMAL: Examining Archival Appraisal in Data-driven Society [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/2befk
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Seyitoğlu, F., & Ivanov, S. H. (2020). Service robots as a tool for physical distancing in tourism [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/k3z6m
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psyarxiv.com psyarxiv.com
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Sakakibara, R., & Ozono, H. (2020). Psychological Research on the COVID-19 Crisis in Japan: Focusing on Infection Preventive Behaviors, Future Prospects, and Information Dissemination Behaviors. https://doi.org/10.31234/osf.io/97zye
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psyarxiv.com psyarxiv.com
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Betsch, C., Korn, L., Sprengholz, P., Felgendreff, L., Eitze, S., Schmid, P., & Böhm, R. (2020). Social and behavioral consequences of mask policies during the COVID-19 pandemic. https://doi.org/10.31234/osf.io/gn6c9
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twitter.com twitter.com
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ReconfigBehSci on Twitter: “brief video describing the https://t.co/zDXjvZFtkM initiative here: https://t.co/8rJEuDj7B4” / Twitter. (n.d.). Twitter. Retrieved July 5, 2020, from https://twitter.com/scibeh/status/1279123525916405762
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twitter.com twitter.com
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ReconfigBehSci on Twitter: “SciBeh now has a video describing our initative! watch, retweet.... https://t.co/j3TF3zfdIt” / Twitter. (n.d.). Twitter. Retrieved June 29, 2020, from https://twitter.com/scibeh/status/1277260447029362688
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www.youtube.com www.youtube.com
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Q&A: Modelling COVID-19. (n.d.). Retrieved June 25, 2020, from https://www.youtube.com/watch?v=HUKC8Wq2a0k
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www.youtube.com www.youtube.comYouTube1
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Supporting Open Science Data Curation, Preservation, and Access by Libraries. (2020, June 25). https://www.youtube.com/watch?v=SbmGWHpzAHs&feature=youtu.be
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twitter.com twitter.com
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Science Magazine on Twitter: “Democrats & Republicans have seemingly taken a divided stance on how to handle the #COVID19 pandemic, & their Twitter accounts might provide the best evidence to date. Watch the latest video from our #coronavirus series on research from @ScienceAdvances: https://t.co/BSCdWS011J https://t.co/sJyF357wje” / Twitter. (n.d.). Twitter. Retrieved June 27, 2020, from https://twitter.com/sciencemagazine/status/1276282194596675590
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sens-public.org sens-public.org
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One of these semiotizing processes is the extraction, interpretation and reintegration of web data from and into human subjectivities.
Machine automation becomes another “subjectivity” or “agentivity”—an influential one, because it is the one filtering and pushing content to humans.
The means of this automated subjectivity is feeding data capitalism: more content, more interaction, more behavioral data produced by the users—data which is then captured (“dispossessed”), extracted, and transformed into prediction services, which render human behavior predictable, and therefore monetizable (Shoshana Zuboff, The Age of Surviellance Capitalism, 2019).
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Uribe-Tirado, A., del Rio, G., Raiher, S., & Ochoa Gutiérrez, J. (2020). Open Science since Covid-19: Open Access + Open Data [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/a5nqw
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osf.io osf.io
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Dunn, M., Stephany, F., Sawyer, S., Munoz, I., Raheja, R., Vaccaro, G., & Lehdonvirta, V. (2020). When Motivation Becomes Desperation: Online Freelancing During the COVID-19 Pandemic [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/67ptf
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osf.io osf.io
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Hossain, M. M., McKyer, E. L. J., & Ma, P. (2020). Applications of artificial intelligence technologies on mental health research during COVID-19 [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/w6c9b
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Brooks, H. Z., Kanjanasaratool, U., Kureh, Y. H., & Porter, M. A. (2020). Disease Detectives: Using Mathematics to Forecast the Spread of Infectious Diseases [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/mvn9z
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stackoverflow.com stackoverflow.com
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all the subcolletions must have the same name, for instance tags
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apps.texastribune.org apps.texastribune.org
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Texas reports over 3,000 total deaths, 10,002 patients hospitalized due to coronavirus. (2020, April 14). The Texas Tribune. https://apps.texastribune.org/features/2020/texas-coronavirus-cases-map/
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osf.io osf.io
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Breznau, N. (2020). The Welfare State and Risk Perceptions: The Novel Coronavirus Pandemic and Public Concern in 70 Countries. https://doi.org/10.31235/osf.io/96fd2
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osf.io osf.io
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Burgess, M. G., Langendorf, R. E., Ippolito, T., & Pielke, R. (2020). Optimistically biased economic growth forecasts and negatively skewed annual variation [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/vndqr
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osf.io osf.io
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Lyttelton, T., Zang, E., & Musick, K. (2020). Gender Differences in Telecommuting and Implications for Inequality at Home and Work. https://doi.org/10.31235/osf.io/tdf8c
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Why Most Advertisers Can’t Afford to Boycott Facebook. (2020, July 8). Pro Market. https://promarket.org/2020/07/08/why-most-advertisers-cant-afford-to-boycott-facebook/
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www.youtube.com www.youtube.com
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DataBeers Torino // Covid-19 online edition. (2020, April 23). https://www.youtube.com/watch?v=g4QPqPFUZLc
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science.sciencemag.org science.sciencemag.org
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Haushofer, J., & Metcalf, C. J. E. (2020). Which interventions work best in a pandemic? Science. https://doi.org/10.1126/science.abb6144
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psyarxiv.com psyarxiv.com
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Adam-Troian, J., & Bagci, S. (2020). The pathogen paradox: Evidence that perceived COVID-19 threat is associated with both pro- and anti-immigrant attitudes. https://doi.org/10.31234/osf.io/948ch
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www.ons.gov.uk www.ons.gov.uk
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Deaths registered weekly in England and Wales, provisional—Office for National Statistics. (n.d.). Retrieved July 9, 2020, from https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/bulletins/deathsregisteredweeklyinenglandandwalesprovisional/weekending26june2020
Tags
Annotators
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www.sciencedirect.com www.sciencedirect.com
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Fontana, M., Iori, M., Montobbio, F., & Sinatra, R. (2020). New and atypical combinations: An assessment of novelty and interdisciplinarity. Research Policy, 49(7), 104063. https://doi.org/10.1016/j.respol.2020.104063
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www.theguardian.com www.theguardian.com
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Spiegelhalter, D. (2020, July 5). Risks, R numbers and raw data: How to interpret coronavirus statistics. The Observer. https://www.theguardian.com/world/2020/jul/05/risks-r-numbers-and-raw-data-how-to-interpret-coronavirus-statistics
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www.medrxiv.org www.medrxiv.org
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Fontanet, A., Tondeur, L., Madec, Y., Grant, R., Besombes, C., Jolly, N., Pellerin, S. F., Ungeheuer, M.-N., Cailleau, I., Kuhmel, L., Temmam, S., Huon, C., Chen, K.-Y., Crescenzo, B., Munier, S., Demeret, C., Grzelak, L., Staropoli, I., Bruel, T., … Hoen, B. (2020). Cluster of COVID-19 in northern France: A retrospective closed cohort study. MedRxiv, 2020.04.18.20071134. https://doi.org/10.1101/2020.04.18.20071134
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www.ncirs.org.au www.ncirs.org.au
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Report: COVID-19 in schools – the experience in NSW | NCIRS. (n.d.). Retrieved July 4, 2020, from http://www.ncirs.org.au/covid-19-in-schools
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Sapoval, N., Mahmoud, M., Jochum, M. D., Liu, Y., Elworth, R. A. L., Wang, Q., Albin, D., Ogilvie, H., Lee, M. D., Villapol, S., Hernandez, K., Berry, I. M., Foox, J., Beheshti, A., Ternus, K., Aagaard, K. M., Posada, D., Mason, C., Sedlazeck, F. J., & Treangen, T. J. (2020). Hidden genomic diversity of SARS-CoV-2: Implications for qRT-PCR diagnostics and transmission. BioRxiv, 2020.07.02.184481. https://doi.org/10.1101/2020.07.02.184481
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www.jclinepi.com www.jclinepi.com
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Sperrin, M., Martin, G. P., Sisk, R., & Peek, N. (2020). Missing data should be handled differently for prediction than for description or causal explanation. Journal of Clinical Epidemiology, 0(0). https://doi.org/10.1016/j.jclinepi.2020.03.028
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jasp-stats.org jasp-stats.org
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Introducing JASP 0.13. (2020, July 2). JASP - Free and User-Friendly Statistical Software. https://jasp-stats.org/?p=6483
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twitter.com twitter.com
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Natalie E. Dean, PhD on Twitter: “THINK LIKE AN EPIDEMIOLOGIST: There are more new confirmed cases each day in the US than at any time during the earlier April peak. But is it really meaningful to compare those numbers? How do epidemiologists decide when to sound the alarm? A thread. 1/11 https://t.co/rPelzIvcxs” / Twitter. (n.d.). Twitter. Retrieved July 3, 2020, from https://twitter.com/nataliexdean/status/1278868210385915904
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COVID-19: Data Summary—NYC Health. (n.d.). Retrieved July 3, 2020, from https://www1.nyc.gov/site/doh/covid/covid-19-data.page
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arxiv.org arxiv.org
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Gupta, H., & Porter, M. A. (2020). Mixed Logit Models and Network Formation. ArXiv:2006.16516 [Physics, Stat]. http://arxiv.org/abs/2006.16516
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gss.civilservice.gov.uk gss.civilservice.gov.uk
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An analyst’s job is never done – GSS. (n.d.). Retrieved July 3, 2020, from https://gss.civilservice.gov.uk/blog/an-analysts-job-is-never-done/
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arxiv.org arxiv.org
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Lovato, J., Allard, A., Harp, R., & Hébert-Dufresne, L. (2020). Distributed consent and its impact on privacy and observability in social networks. ArXiv:2006.16140 [Physics]. http://arxiv.org/abs/2006.16140
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psyarxiv.com psyarxiv.com
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Rahman, M., Ali, G. G. M. N., Li, X. J., Paul, K. C., & Chong, P. H. J. (2020). Twitter and Census Data Analytics to Explore Socioeconomic Factors for Post-COVID-19 Reopening Sentiment [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/fz4ry
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www.nature.com www.nature.com
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Lavezzo, E., Franchin, E., Ciavarella, C., Cuomo-Dannenburg, G., Barzon, L., Del Vecchio, C., Rossi, L., Manganelli, R., Loregian, A., Navarin, N., Abate, D., Sciro, M., Merigliano, S., De Canale, E., Vanuzzo, M. C., Besutti, V., Saluzzo, F., Onelia, F., Pacenti, M., … Crisanti, A. (2020). Suppression of a SARS-CoV-2 outbreak in the Italian municipality of Vo’. Nature, 1–1. https://doi.org/10.1038/s41586-020-2488-1
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psyarxiv.com psyarxiv.com
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Rauschenberg, C., Schick, A., Goetzl, C., Röhr, S., Riedel-Heller, S., Koppe, G., Durstewitz, D., Krumm, S., & Reininghaus, U. (2020). Social isolation, mental health and use of digital interventions in youth during the COVID-19 pandemic: A nationally representative survey [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/v64hf
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psyarxiv.com psyarxiv.com
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Levita, L., Gibson Miller, J., Hartman, T. K., Murphy, J., Shevlin, M., McBride, O., Mason, L., Martinez, A. P., bennett, kate m, Stocks, T. V. A., McKay, R., & Bentall, R. (2020). Report2: Impact of Covid-19 on young people aged 13-24 in the UK- preliminary findings [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/s32j8
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psyarxiv.com psyarxiv.com
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Yamada, Y. (2020). Micropublishing during and after the COVID-19 era [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/8fum4
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medium.com medium.com
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Caching is dangerous if not done correctly. For example, making decisions based on outdated data as if it was current.
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Czarnek, G., Szwed, P., & Kossowska, M. (2020). Political ideology and attitudes toward vaccination: Study report. https://doi.org/10.31234/osf.io/uwehk
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psyarxiv.com psyarxiv.com
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Im, H., & Chen, C. (2020). Social Distancing Around the Globe: Cultural Correlates of Reduced Mobility [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/b2s37
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www.newscientist.com www.newscientist.comR number1
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Vaughan, A. (n.d.). R number. New Scientist. Retrieved June 29, 2020, from https://www.newscientist.com/term/r-number/
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psyarxiv.com psyarxiv.com
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Syed, M., & Donnellan, B. (2020). Registered Reports with Developmental and Secondary Data: Some Brief Observations and Introduction to the Special Issue [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/gnhxk
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zoom.us zoom.us
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Welcome! You are invited to join a webinar: Supporting Open Science Data Curation, Preservation, and Access by Libraries. After registering, you will receive a confirmation email about joining the webinar. (n.d.). Zoom Video. Retrieved June 28, 2020, from https://zoom.us/webinar/register/2615905946283/WN_W6dYUXQFTqGQjGAZPRB74w
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www.sciencedirect.com www.sciencedirect.com
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Rosenberg, E. S., Tesoriero, J. M., Rosenthal, E. M., Chung, R., Barranco, M. A., Styer, L. M., Parker, M. M., John Leung, S.-Y., Morne, J. E., Greene, D., Holtgrave, D. R., Hoefer, D., Kumar, J., Udo, T., Hutton, B., & Zucker, H. A. (2020). Cumulative incidence and diagnosis of SARS-CoV-2 infection in New York. Annals of Epidemiology. https://doi.org/10.1016/j.annepidem.2020.06.004
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www.unforgettable.me www.unforgettable.me
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psyarxiv.com psyarxiv.com
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Bulbulia, J., Barlow, F., Davis, D. E., Greaves, L., Highland, B., Houkamau, C., Milfont, T. L., Osborne, D., Piven, S., Shaver, J., Troughton, G., Wilson, M., Yogeeswaran, K., & Sibley, C. G. (2020). National Longitudinal Investigation of COVID-19 Lockdown Distress Clarifies Mechanisms of Mental Health Burden and Relief [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/cswde
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- scientific practice
- is:blog
- ethics
- lang:en
- COVID-19
- data collection
- study design
- technique
- qualitative research
- pandemic
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blogs.lse.ac.uk blogs.lse.ac.uk
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n this project we see a shift from a citizen-based model to a consumer model for urban planning, where all citizens’ ‘personal and environmental data is an economic resource.’
Called survillance capitlism
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reutersinstitute.politics.ox.ac.uk reutersinstitute.politics.ox.ac.uk
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Newman, N. (n.d.). Reuters Institute Digital News Report 2020. 112.
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Local file Local file
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Informal mentorship was captured using the following retrospective question from Wave 3 of the AddHealth data: "Other than your parents or step-parents, has an adult made an important positive difference in your life at any time since you were 14 years old?" Based on this question, I created a binary indicator for mentorship coded 1 if the young person had an informal mentor and 0 if they did not. Respondents were then asked "How is this person related to you?", and given response options like "family,""teacher/counselor,""friend's parent,""neighbor,"and "religious leader.
Defining informal mentorship in the survey data
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Middle-income subsample 3,158
Middle-income subsample for analysis was 3,158
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1. "Middle-income" is defined as anyone living in a household making two-thirds to double the median income (Pew Research Center, 2016). In 1994, the median income for a family of four was $46,757(US Bureau of Statistics, 1996). Thus, "middle-income" families would be those making between $30,860 and $93,514. Because I only have data available in $25,000 increments, I am defining middle-income families as those making between $25,000 and $100,000 a year in Wave 1.
Middle-income = families making $25k-$100k a year in Wave 1
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Defining low-,middle-, and high-income groupsDue to the limitation in the data described above, all incomes had to be converted in to categorical responses, with the smallest possible category size of $25,000 dollars. This created five categories for all incomes:
Defining income groups: under $25k, $25k-$49999, $50k-$74999, $75k-$99999, and $100k+.
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