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papers.ssrn.com papers.ssrn.com
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Krupenkin, Masha, Kai Zhu, Dylan Walker, and David M. Rothschild. ‘If a Tree Falls in the Forest: COVID-19, Media Choices, and Presidential Agenda Setting’. SSRN Scholarly Paper. Rochester, NY: Social Science Research Network, 22 September 2020. https://doi.org/10.2139/ssrn.3697069.
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www.sciencedirect.com www.sciencedirect.com
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Goolsbee, Austan, and Chad Syverson. ‘Fear, Lockdown, and Diversion: Comparing Drivers of Pandemic Economic Decline 2020’. Journal of Public Economics 193 (1 January 2021): 104311. https://doi.org/10.1016/j.jpubeco.2020.104311.
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McCabe, Stefan, Leo Torres, Timothy LaRock, Syed Arefinul Haque, Chia-Hung Yang, Harrison Hartle, and Brennan Klein. ‘Netrd: A Library for Network Reconstruction and Graph Distances’. ArXiv:2010.16019 [Physics], 29 October 2020. http://arxiv.org/abs/2010.16019.
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Increasing the impact of health research through co-production of knowledge | The BMJ. (n.d.). Retrieved 16 February 2021, from https://www.bmj.com/co-producing-knowledge?utm_source=twitter&utm_medium=social&utm_term=hootsuite&utm_content=sme&utm_campaign=usage
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arxiv.org arxiv.org
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Hota, Ashish R., Tanya Sneh, and Kavish Gupta. ‘Impacts of Game-Theoretic Activation on Epidemic Spread over Dynamical Networks’. ArXiv:2011.00445 [Physics], 1 November 2020. http://arxiv.org/abs/2011.00445.
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Malta, Monica. ‘My Journey with COVID-19’. EClinicalMedicine 27 (1 October 2020). https://doi.org/10.1016/j.eclinm.2020.100599.
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arxiv.org arxiv.org
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Kozlowski, Diego, Jennifer Dusdal, Jun Pang, and Andreas Zilian. ‘Semantic and Relational Spaces in Science of Science: Deep Learning Models for Article Vectorisation’. ArXiv:2011.02887 [Physics], 5 November 2020. http://arxiv.org/abs/2011.02887.
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academic.oup.com academic.oup.com
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Blakely, Tony, John Lynch, Koen Simons, Rebecca Bentley, and Sherri Rose. ‘Reflection on Modern Methods: When Worlds Collide—Prediction, Machine Learning and Causal Inference’. International Journal of Epidemiology 49, no. 6 (1 December 2020): 2058–64. https://doi.org/10.1093/ije/dyz132.
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Wise, J. (2021). Covid-19: Extra 1.7 million people in England are asked to shield. BMJ, 372, n467. https://doi.org/10.1136/bmj.n467
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To end covid-19, we must end discrimination and inequality. (2021, March 1). The BMJ. https://blogs.bmj.com/bmj/2021/03/01/to-end-covid-19-we-must-end-discrimination-and-inequality/
Tags
- discrimination
- global population
- public health
- COVID-19
- global health
- public policy
- health
- healthcare
- reduction
- goal
- health policy
- inequality
- sustainable development
- lang:en
- crisis
- is:article
- human development
- government
- pandemic
- global
- pledge
- policy
- community
- country
- vulnerable
- law
Annotators
URL
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Damialis, A., Gilles, S., Sofiev, M., Sofieva, V., Kolek, F., Bayr, D., Plaza, M. P., Leier-Wirtz, V., Kaschuba, S., Ziska, L. H., Bielory, L., Makra, L., Trigo, M. del M., Group, C.-19/POLLEN study, & Traidl-Hoffmann, C. (2021). Higher airborne pollen concentrations correlated with increased SARS-CoV-2 infection rates, as evidenced from 31 countries across the globe. Proceedings of the National Academy of Sciences, 118(12). https://doi.org/10.1073/pnas.2019034118
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Yang, K.-C., Pierri, F., Hui, P.-M., Axelrod, D., Torres-Lugo, C., Bryden, J., & Menczer, F. (2020). The COVID-19 Infodemic: Twitter versus Facebook. ArXiv:2012.09353 [Cs]. http://arxiv.org/abs/2012.09353
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Heroy, Samuel, Isabella Loaiza, Alexander Pentland, and Neave O’Clery. ‘Controlling COVID-19: Labor Structure Is More Important than Lockdown Policy’. ArXiv:2010.14630 [Physics], 5 November 2020. http://arxiv.org/abs/2010.14630.
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science.sciencemag.org science.sciencemag.org
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Buss, Lewis F., Carlos A. Prete, Claudia M. M. Abrahim, Alfredo Mendrone, Tassila Salomon, Cesar de Almeida-Neto, Rafael F. O. França, et al. ‘Three-Quarters Attack Rate of SARS-CoV-2 in the Brazilian Amazon during a Largely Unmitigated Epidemic’. Science 371, no. 6526 (15 January 2021): 288–92. https://doi.org/10.1126/science.abe9728.
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Hidiroglu, S., Ay, P., Topuzoglu, A., Kalafat, C., & Karavus, M. (2010). Resistance to vaccination: The attitudes and practices of primary healthcare workers confronting the H1N1 pandemic. Vaccine, 28(51), 8120–8124. https://doi.org/10.1016/j.vaccine.2010.09.104
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Impact of Social Sciences. ‘How to Run an Academic Writing Retreat and Bring the Campus Back Together’, 9 November 2020. https://blogs.lse.ac.uk/impactofsocialsciences/2020/11/09/how-to-run-an-academic-writing-retreat-and-bring-the-campus-back-together/.
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Witze, Alexandra. ‘What NASA Missions Can Teach Us about Teamwork’. Nature 587, no. 7834 (16 November 2020): 359–60. https://doi.org/10.1038/d41586-020-03222-3.
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www.bmj.com www.bmj.com
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Fowler, J. H., & Christakis, N. A. (2008). Dynamic spread of happiness in a large social network: Longitudinal analysis over 20 years in the Framingham Heart Study. BMJ, 337, a2338. https://doi.org/10.1136/bmj.a2338
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Biggs, A. T., & Littlejohn, L. F. (2021). Revisiting the initial COVID-19 pandemic projections. The Lancet Microbe, 2(3), e91–e92. https://doi.org/10.1016/S2666-5247(21)00029-X
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Mims, C. (2020, November 21). Four Reasons the Stay-at-Home Economy Is Here to Stay. Wall Street Journal. https://www.wsj.com/articles/four-reasons-the-stay-at-home-economy-is-here-to-stay-11605934806
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Kao, R. Z., Paul Mozur,Aaron Krolik,Jeff. (n.d.). Leaked Documents Show How China’s Army of Paid Internet Trolls Helped Censor the Coronavirus. ProPublica. Retrieved 2 March 2021, from https://www.propublica.org/article/leaked-documents-show-how-chinas-army-of-paid-internet-trolls-helped-censor-the-coronavirus
Tags
- China
- virus
- outbreak
- COVID-19
- misinformation
- social media
- is:article
- government
- pandemic
- media
- internet
- policy
- censor
- propaganda
- lang:en
Annotators
URL
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www.bmj.com www.bmj.com
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Iacobucci, G. (2021). Sixty seconds on. . . Flu. BMJ, 372, n584. https://doi.org/10.1136/bmj.n584
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www.nature.com www.nature.com
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Heyman, T., Moors, P., & Rabagliati, H. (2020). The benefits of adversarial collaboration for commentaries. Nature Human Behaviour, 4(12), 1217–1217. https://doi.org/10.1038/s41562-020-00978-6
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gh.bmj.com gh.bmj.com
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Ii, Y. B., Ouattara, A., Torreele, E., & Okonta, C. (2021). How to ensure a needs-driven and community-centred vaccination strategy for COVID-19 in Africa. BMJ Global Health, 6(2), e005306. https://doi.org/10.1136/bmjgh-2021-005306
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www.bloomberg.com www.bloomberg.com
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Covid-19 Isn’t the Only Thing Shortening American Lives. (2021, February 23). Bloomberg.Com. https://www.bloomberg.com/opinion/articles/2021-02-23/covid-19-isn-t-the-only-thing-shortening-american-lives
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Owens, C. (n.d.). Republicans are least likely to want the coronavirus vaccine. Axios. Retrieved 2 March 2021, from https://www.axios.com/republicans-coronavirus-vaccine-hesitancy-023bf32f-3d68-4206-b906-4f701b87c39f.html
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Søe, S. O. (2019). A unified account of information, misinformation, and disinformation. Synthese. https://doi.org/10.1007/s11229-019-02444-x
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Abbasi, K. (2020). The curious case of the Danish mask study. BMJ, 371, m4586. https://doi.org/10.1136/bmj.m4586
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Haug, N., Geyrhofer, L., Londei, A., Dervic, E., Desvars-Larrive, A., Loreto, V., Pinior, B., Thurner, S., & Klimek, P. (2020). Ranking the effectiveness of worldwide COVID-19 government interventions. Nature Human Behaviour, 4(12), 1303–1312. https://doi.org/10.1038/s41562-020-01009-0
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Peyton, Kyle, Gregory A. Huber, and Alexander Coppock. “The Generalizability of Online Experiments Conducted During The COVID-19 Pandemic.” SocArXiv, November 28, 2020. https://doi.org/10.31235/osf.io/s45yg.
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Partha, D., & David, P. A. (1994). Toward a new economics of science. Research Policy, 23(5), 487–521. https://doi.org/10.1016/0048-7333(94)01002-1
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Chwalisz, C. (2021). The pandemic has pushed citizen panels online. Nature, 589(7841), 171–171. https://doi.org/10.1038/d41586-021-00046-7
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Oliver, D. (2020). Covid-19: Hospital discharges during pandemic were often chaotic, says watchdog. BMJ, 371, m4155. https://doi.org/10.1136/bmj.m4155
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Mathai, V., Das, A., Bailey, J. A., & Breuer, K. (2021). Airflows inside passenger cars and implications for airborne disease transmission. Science Advances, 7(1), eabe0166. https://doi.org/10.1126/sciadv.abe0166
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Gordon, D. E., Hiatt, J., Bouhaddou, M., Rezelj, V. V., Ulferts, S., Braberg, H., Jureka, A. S., Obernier, K., Guo, J. Z., Batra, J., Kaake, R. M., Weckstein, A. R., Owens, T. W., Gupta, M., Pourmal, S., Titus, E. W., Cakir, M., Soucheray, M., McGregor, M., … Krogan, N. J. (2020). Comparative host-coronavirus protein interaction networks reveal pan-viral disease mechanisms. Science, 370(6521). https://doi.org/10.1126/science.abe9403
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