Methodology To determine the link between heat and income in U.S. cities, NPR used NASA satellite imagery and U.S. Census American Community Survey data. An open-source computer program developed by NPR downloaded median household income data for census tracts in the 100 most populated American cities, as well as geographic boundaries for census tracts. NPR combined these data with TIGER/Line shapefiles of the cities.
This is an excellent example of data journalism.
Solid’s State primitive is arguably its most powerful and distinctive one. Through the use of proxies and explicit setters it gives the control of an immutable interface and the performance of a mutable one
In contrast, data is just mutated in Vue.
We have to be careful not to mutate state so when we have some complex state like an object or an array we have to use some ugly tricks like in the setTodoCompleted function above.
Shauna Brail on Twitter. (n.d.). Twitter. Retrieved October 9, 2020, from https://twitter.com/shaunabrail/status/1313818873163067392
Stix, Y. Z., Gary. (n.d.). COVID-19 Is Now the Third Leading Cause of Death in the U.S. Scientific American. Retrieved October 9, 2020, from https://www.scientificamerican.com/article/covid-19-is-now-the-third-leading-cause-of-death-in-the-u-s1/
Note that interacting with these <input> elements will mutate the array. If you prefer to work with immutable data, you should avoid these bindings and use event handlers instead.
use-methods is built on immer, which allows you to write your methods in an imperative, mutating style, even though the actual state managed behind the scenes is immutable.
NIH VideoCast—Joseph Leiter NLM/MLA Lectureship: Digital Epidemiology and the COVID-19 Pandemic. (n.d.). Retrieved 6 October 2020, from https://videocast.nih.gov/watch=38269
Fionna O’Leary, 🕯 on Twitter. (n.d.). Twitter. Retrieved October 6, 2020, from https://twitter.com/fascinatorfun/status/1312855480956575744
IZA – Institute of Labor Economics. ‘COVID-19 and the Labor Market’. Accessed 6 October 2020. https://covid-19.iza.org/publications/dp13737/.
IZA – Institute of Labor Economics. ‘COVID-19 and the Labor Market’. Accessed 6 October 2020. https://covid-19.iza.org/publications/dp13690/.
1.1. Monitors For the purposes of AQS, a monitor does not refer to a specific piece of equipment. Instead, it reflects that a given pollutant (or other parameter) is being measured at a given site. Identified by: The site (state + county + site number) where the monitor is located AND The pollutant code AND POC – Parameter Occurrence Code. Used to uniquely identify a monitor if there is more than one device measuring the same pollutant at the same site. For example monitor IDs are usually written in the following way: SS-CCC-NNNN-PPPPP-Q where SS is the State FIPS code, CCC is the County FIPS code, and NNNN is the Site Number within the county (leading zeroes are always included for these fields), PPPPP is the AQS 5-digit parameter code, and Q is the POC. For example: 01-089-0014-44201-2 is Alabama, Madison County, Site Number 14, ozone monitor, POC 2.
How monitors (specific measures of specific criteria) are identified in AQS data.
2019nCOV. (n.d.). MOBS Lab. Retrieved October 2, 2020, from https://www.mobs-lab.org/2019ncov.html
Karatayev, Vadim A., Madhur Anand, and Chris T. Bauch. ‘Local Lockdowns Outperform Global Lockdown on the Far Side of the COVID-19 Epidemic Curve’. Proceedings of the National Academy of Sciences 117, no. 39 (29 September 2020): 24575–80. https://doi.org/10.1073/pnas.2014385117.
2020 Conference on Computational Sociology | IRiSS. (n.d.). Retrieved 30 September 2020, from https://iriss.stanford.edu/css/conferences/2020-conference-computational-sociology
Computational Social Science to Address the (Post) COVID-19 Reality. (2020, June 27). https://www.youtube.com/watch?v=7d-Dq0e1JJ0&list=PL9UNgBC7ODr6eZkwB6W0QSzpDs46E8WPN&index=4
Thacker, P. D. (2020). A few tiny steps towards transparency: How the Sunshine Act shone light on industry’s influence in medicine. BMJ, 370. https://doi.org/10.1136/bmj.m3229
Harvard’s Chetty Finds Economic Carnage in Wealthiest ZIP Codes. (2020, September 24). Bloomberg.Com. https://www.bloomberg.com/news/features/2020-09-24/harvard-economist-raj-chetty-creates-god-s-eye-view-of-pandemic-damage
Knawy, B. A., Adil, M., Crooks, G., Rhee, K., Bates, D., Jokhdar, H., Klag, M., Lee, U., Mokdad, A. H., Schaper, L., Hazme, R. A., Khathaami, A. M. A., & Abduljawad, J. (2020). The Riyadh Declaration: The role of digital health in fighting pandemics. The Lancet, 0(0). https://doi.org/10.1016/S0140-6736(20)31978-4
Tim spector on Twitter. (n.d.). Twitter. Retrieved September 25, 2020, from https://twitter.com/timspector/status/1308873677807792129
Online Research: From Funding to Data Collection. (n.d.). Association for Psychological Science - APS. Retrieved September 25, 2020, from https://www.psychologicalscience.org/news/online-research.html
"The Data Visualisation Catalogue is a project developed by Severino Ribecca to create a library of different information visualisation types." I like the explanations of when one might use a particular type of data visualization to highlight - or obscure! - what the data is saying.
Ruktanonchai, N. W., Floyd, J. R., Lai, S., Ruktanonchai, C. W., Sadilek, A., Rente-Lourenco, P., Ben, X., Carioli, A., Gwinn, J., Steele, J. E., Prosper, O., Schneider, A., Oplinger, A., Eastham, P., & Tatem, A. J. (2020). Assessing the impact of coordinated COVID-19 exit strategies across Europe. Science, 369(6510), 1465–1470. https://doi.org/10.1126/science.abc5096
Nagaraj, A., Shears, E., & Vaan, M. de. (2020). Improving data access democratizes and diversifies science. Proceedings of the National Academy of Sciences, 117(38), 23490–23498. https://doi.org/10.1073/pnas.2001682117
The RDF model encodes data in the form ofsubject,predicate,objecttriples. The subjectand object of a triple are both URIs that each identify a resource, or a URI and a stringliteral respectively. The predicate specifies how the subject and object are related, and isalso represented by a URI.
Basic description of Resource Description Framework
Facebook ignored or was slow to act on evidence that fake accounts on its platform have been undermining elections and political affairs around the world, according to an explosive memo sent by a recently fired Facebook employee and obtained by BuzzFeed News.The 6,600-word memo, written by former Facebook data scientist Sophie Zhang, is filled with concrete examples of heads of government and political parties in Azerbaijan and Honduras using fake accounts or misrepresenting themselves to sway public opinion. In countries including India, Ukraine, Spain, Brazil, Bolivia, and Ecuador, she found evidence of coordinated campaigns of varying sizes to boost or hinder political candidates or outcomes, though she did not always conclude who was behind them.
(((Howard Forman))) on Twitter. (n.d.). Twitter. Retrieved September 23, 2020, from https://twitter.com/thehowie/status/1308107599682756609
Graham Cooke on Twitter. (n.d.). Twitter. Retrieved September 23, 2020, from https://twitter.com/grahamscooke/status/1308132497822281728
Obradovich, N., Özak, Ö., Martín, I., Ortuño-Ortín, I., Awad, E., Cebrián, M., Cuevas, R., Desmet, K., Rahwan, I., & Cuevas, Á. (2020). Expanding the measurement of culture with a sample of two billion humans [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/qkf42
Romanini, Daniele, Sune Lehmann, and Mikko Kivelä. ‘Privacy and Uniqueness of Neighborhoods in Social Networks’. ArXiv:2009.09973 [Physics], 21 September 2020. http://arxiv.org/abs/2009.09973.
Provides state management for tree-like components. Handles building a collection of items from props, item expanded state, and manages multiple selection state.
Adam Kucharski on Twitter. (n.d.). Twitter. Retrieved September 22, 2020, from https://twitter.com/AdamJKucharski/status/1307231588732764161
Friston, K., Costello, A., & Pillay, D. (2020). Dark matter, second waves and epidemiological modelling. MedRxiv, 2020.09.01.20185876. https://doi.org/10.1101/2020.09.01.20185876
Carl T. Bergstrom on Twitter. (n.d.). Twitter. Retrieved September 22, 2020, from https://twitter.com/CT_Bergstrom/status/1306995362368954369
Kyle Griffin on Twitter. (n.d.). Twitter. Retrieved September 22, 2020, from https://twitter.com/kylegriffin1/status/1307343837891833861
Holman, E. A., Thompson, R. R., Garfin, D. R., & Silver, R. C. (2020). The unfolding COVID-19 pandemic: A probability-based, nationally representative study of mental health in the U.S. Science Advances, eabd5390. https://doi.org/10.1126/sciadv.abd5390
Nic Fildes in London and Javier Espinoza in Brussels April 8 2020 Jump to comments section Print this page Be the first to know about every new Coronavirus story Get instant email alerts When the World Health Organization launched a 2007 initiative to eliminate malaria on Zanzibar, it turned to an unusual source to track the spread of the disease between the island and mainland Africa: mobile phones sold by Tanzania’s telecoms groups including Vodafone, the UK mobile operator.Working together with researchers at Southampton university, Vodafone began compiling sets of location data from mobile phones in the areas where cases of the disease had been recorded. Mapping how populations move between locations has proved invaluable in tracking and responding to epidemics. The Zanzibar project has been replicated by academics across the continent to monitor other deadly diseases, including Ebola in west Africa.“Diseases don’t respect national borders,” says Andy Tatem, an epidemiologist at Southampton who has worked with Vodafone in Africa. “Understanding how diseases and pathogens flow through populations using mobile phone data is vital.”
the best way to track the spread of the pandemic is to use heatmaps built on data of multiple phones which, if overlaid with medical data, can predict how the virus will spread and determine whether government measures are working.
Transport use during the coronavirus (COVID-19) pandemic. (n.d.). GOV.UK. Retrieved September 18, 2020, from https://www.gov.uk/government/statistics/transport-use-during-the-coronavirus-covid-19-pandemic
Graphs and maps from EUROMOMO. (n.d.). EUROMOMO. Retrieved September 18, 2020, from https://euromomo.eu/dev-404-page/
Svelte offers an immutable way — but it’s just a mask to hide “assignment”, because assignment triggers an update, but not immutability. So it’s enough to write todos=todos, after that Svelte triggers an update.
Like with React, you can pass in callback props like onSave and onDelete, which is the main way you send data out of a component to a parent.
COVID-19 reports. (n.d.). Imperial College London. Retrieved September 17, 2020, from http://www.imperial.ac.uk/medicine/departments/school-public-health/infectious-disease-epidemiology/mrc-global-infectious-disease-analysis/covid-19/covid-19-reports/
Giles, J. R., Erbach-Schoenberg, E. zu, Tatem, A. J., Gardner, L., Bjørnstad, O. N., Metcalf, C. J. E., & Wesolowski, A. (2020). The duration of travel impacts the spatial dynamics of infectious diseases. Proceedings of the National Academy of Sciences, 117(36), 22572–22579. https://doi.org/10.1073/pnas.1922663117
React is an isomorphic/universal framework. That means that there is a virtual representation of the UI component tree, and that is separate from the actual rendering that it outputs in the browser.
How to Export Your Content If you log into Graphite before August 15th, you can download each file in any of the available formats offered. If you'd like a bulk download, I recommend (for the technically inclined) using the exporter tool I created. For those less technically inclined, Blockstack may have some options for you. Remember, Graphite never owned your content. Never had control of your content. And that was the real power of its offering.
you should take care not to mutate the passed in value
Moreau, D., & Gamble, B. (2020). Conducting a meta-analysis in the age of open science: Tools, tips, and practical recommendations. Psychological Methods, No Pagination Specified-No Pagination Specified. https://doi.org/10.1037/met0000351
The COVID Tracking Project on Twitter. (n.d.). Twitter. Retrieved September 16, 2020, from https://twitter.com/COVID19Tracking/status/1304910646404739073
Krista Fischer on Twitter. (n.d.). Twitter. Retrieved September 15, 2020, from https://twitter.com/kristafischer16/status/1305145951955423233
Max Primbs on Twitter. (n.d.). Twitter. Retrieved September 14, 2020, from https://twitter.com/MaxPrimbs/status/1304516869509066760
Gollwitzer, M., Abele-Brehm, A., Fiebach, C., Ramthun, R., Scheel, A. M., Schönbrodt, F., & Steinberg, U. (2020). Data Management and Data Sharing in Psychological Science: Revision of the DGPs Recommendations. https://doi.org/10.31234/osf.io/24ncs
Finding data
You're right about data here. I follow some research out of the MIT Media lab by Cesar Hidalgo who may have some interesting data resources if you poke around.
Some additional starting points:
In this app, we have a <Hoverable> component that tracks whether the mouse is currently over it. It needs to pass that data back to the parent component, so that we can update the slotted contents. For this, we use slot props.
Stuart mcdonald on Twitter. (n.d.). Twitter. Retrieved September 10, 2020, from https://twitter.com/ActuaryByDay/status/1303719422595682306
Rajkumar, R. P. (2020). Novel Coronavirus Disease (COVID-19) and Suicide: Conceptual and Practical Considerations [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/z7drs
Spiegelhalter, D. (2020). Use of “normal” risk to improve understanding of dangers of covid-19. BMJ, 370. https://doi.org/10.1136/bmj.m3259
Susan Athey, July 22, 2020. (2020, August 2). https://www.youtube.com/watch?v=hqTOPrUxDzM
We wanted a library designed specifically for a functional programming style, one that makes it easy to create functional pipelines, one that never mutates user data.
Hu, Y., & Wang, R.-Q. (2020). Understanding the removal of precise geotagging in tweets. Nature Human Behaviour, 1–3. https://doi.org/10.1038/s41562-020-00949-x
COVID-19. (n.d.). Retrieved September 7, 2020, from https://covid19.healthdata.org/united-states-of-america?view=total-deaths&tab=trend
COVID Projections Tracker. (n.d.). Retrieved September 7, 2020, from https://www.covid-projections.com/
Johan Hellström on Twitter. (n.d.). Twitter. Retrieved September 7, 2020, from https://twitter.com/jhnhellstrom/status/1301073768748593153
NW, 1615 L. St, Suite 800Washington, & Inquiries, D. 20036USA202-419-4300 | M.-857-8562 | F.-419-4372 | M. (n.d.). A majority of young adults in the U.S. live with their parents for the first time since the Great Depression. Pew Research Center. Retrieved September 7, 2020, from https://www.pewresearch.org/fact-tank/2020/09/04/a-majority-of-young-adults-in-the-u-s-live-with-their-parents-for-the-first-time-since-the-great-depression/
Carozzi, F., Provenzano, S., Roth, S. (2020). Urban Density and Covid-19. Retrieved from http://cep.lse.ac.uk/pubs/download/dp1711.pdf
Had it not been for the attentiveness of one person who went beyond the task of classifying galaxies into predetermined categories and was able to communicate this to the researchers via the online forum, what turned out to be important new phenomena might have gone undiscovered.
Sometimes our attempts to improve data quality in citizen science projects can actually work against us. Pre-determined categories and strict regulations could prevent the reporting of important outliers.
COVID-19 Symptom Survey—Request for Data Access. (n.d.). Facebook Data for Good. Retrieved May 29, 2020, from https://dataforgood.fb.com/docs/covid-19-symptom-survey-request-for-data-access/
ReconfigBehSci on Twitter: “RT @ScottGottliebMD: See how quickly you can find Sweden on this map.... https://t.co/bhXACObtnQ” / Twitter. (n.d.). Twitter. Retrieved June 29, 2020, from https://twitter.com/scibeh/status/1276799757575315457
Spinney, L. (2020, May 31). Covid-19 expert Karl Friston: “Germany may have more immunological ‘dark matter.’” The Observer. https://www.theguardian.com/world/2020/may/31/covid-19-expert-karl-friston-germany-may-have-more-immunological-dark-matter
aaronpeikert. (2020). Aaronpeikert/reproducible-research [TeX]. https://github.com/aaronpeikert/reproducible-research (Original work published 2019)
Building the New Economy · Works in Progress. (n.d.). Works in Progress. Retrieved June 16, 2020, from https://wip.mitpress.mit.edu/new-economy
Sixth Report. (2020, June 19). COVID-19 Mobility Monitoring Project. https://covid19mm.github.io//in-progress/2020/06/19/sixth-report.html
This is probably one of the biggest things to get used to in React – this flow where data goes out and then back in.
Very good project ... really the best thought out data grid.
Desi Rodriguez-Lonebear, PhD on Twitter. (n.d.). Twitter. Retrieved 2 September 2020, from https://twitter.com/native4data/status/1300950878082531329
Steven Goodman: Statistical methods as social technologies versus analytic tools: Implications for metascience and research reform (Video). (n.d.). Metascience.com. Retrieved 2 September 2020, from https://metascience.com/events/metascience-2019-symposium/steven-goodman-statistical-methods-versus-analytic-tools/
Ali, A. (2020, August 28). Visualizing the Social Media Universe in 2020. Visual Capitalist. https://www.visualcapitalist.com/visualizing-the-social-media-universe-in-2020/
Bhatia, S., Walasek, L., Slovic, P., & Kunreuther, H. (2020). The More Who Die, the Less We Care: Evidence from Natural Language Analysis of Online News Articles and Social Media Posts. Risk Analysis, risa.13582. https://doi.org/10.1111/risa.13582
Harford, Tim. ‘A Bluffer’s Guide to Surviving Covid-19 | Free to Read’, 28 August 2020. https://www.ft.com/content/176b9bbe-56cf-4428-a0cd-070db2d8e6ff.
Chaudhry, R., Dranitsaris, G., Mubashir, T., Bartoszko, J., & Riazi, S. (2020). A country level analysis measuring the impact of government actions, country preparedness and socioeconomic factors on COVID-19 mortality and related health outcomes. EClinicalMedicine, 0(0). https://doi.org/10.1016/j.eclinm.2020.100464
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van Smeden, M., Lash, T. L., & Groenwold, R. H. H. (2020). Reflection on modern methods: Five myths about measurement error in epidemiological research. International Journal of Epidemiology, 49(1), 338–347. https://doi.org/10.1093/ije/dyz251
Lozano, R., Fullman, N., Mumford, J. E., Knight, M., Barthelemy, C. M., Abbafati, C., Abbastabar, H., Abd-Allah, F., Abdollahi, M., Abedi, A., Abolhassani, H., Abosetugn, A. E., Abreu, L. G., Abrigo, M. R. M., Haimed, A. K. A., Abushouk, A. I., Adabi, M., Adebayo, O. M., Adekanmbi, V., … Murray, C. J. L. (2020). Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019: A systematic analysis for the Global Burden of Disease Study 2019. The Lancet, 0(0). https://doi.org/10.1016/S0140-6736(20)30750-9
GDP and employment flash estimates for the second quarter of 2020: GDP down by 12.1% and employment down by 2.8% in the euro area. (n.d.). Retrieved August 29, 2020, from https://ec.europa.eu/eurostat/web/products-press-releases/-/2-14082020-AP
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Ray, E. L., Wattanachit, N., Niemi, J., Kanji, A. H., House, K., Cramer, E. Y., Bracher, J., Zheng, A., Yamana, T. K., Xiong, X., Woody, S., Wang, Y., Wang, L., Walraven, R. L., Tomar, V., Sherratt, K., Sheldon, D., Reiner, R. C., Prakash, B. A., … Consortium, C.-19 F. H. (2020). Ensemble Forecasts of Coronavirus Disease 2019 (COVID-19) in the U.S. MedRxiv, 2020.08.19.20177493. https://doi.org/10.1101/2020.08.19.20177493
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Marijon, E., Karam, N., Jost, D., Perrot, D., Frattini, B., Derkenne, C., Sharifzadehgan, A., Waldmann, V., Beganton, F., Narayanan, K., Lafont, A., Bougouin, W., & Jouven, X. (2020). Out-of-hospital cardiac arrest during the COVID-19 pandemic in Paris, France: A population-based, observational study. The Lancet Public Health, 5(8), e437–e443. https://doi.org/10.1016/S2468-2667(20)30117-1
Basellini, U., Alburez-Gutierrez, D., Del Fava, E., Perrotta, D., Bonetti, M., Camarda, C. G., & Zagheni, E. (2020). Linking excess mortality to Google mobility data during the COVID-19 pandemic in England and Wales [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/75d6m
Fell, M. J., Pagel, L., Chen, C., Goldberg, M. H., Herberz, M., Huebner, G., Sareen, S., & Hahnel, U. J. J. (2020). Validity of energy social research during and after COVID-19: Challenges, considerations, and responses [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/pe6cd
The Trump administration must stop sidelining the CDC. (2020). Nature, 583(7818), 660–660. https://doi.org/10.1038/d41586-020-02231-6
Santosh, R., Guntuku, S. C., Schwartz, H., Eichstaedt, J., & Ungar, L. (2020). Detecting Symptoms using Context-based Twitter Embeddings during COVID-19. https://openreview.net/forum?id=DFJhXXPZrM7
A Literature Review of the Economics of COVID-19. COVID-19 and the Labor Market. (n.d.). IZA – Institute of Labor Economics. Retrieved July 31, 2020, from https://covid-19.iza.org/publications/dp13411/
Holtz, D., Zhao, M., Benzell, S. G., Cao, C. Y., Rahimian, M. A., Yang, J., Allen, J., Collis, A., Moehring, A., Sowrirajan, T., Ghosh, D., Zhang, Y., Dhillon, P. S., Nicolaides, C., Eckles, D., & Aral, S. (2020). Interdependence and the cost of uncoordinated responses to COVID-19. Proceedings of the National Academy of Sciences, 117(33), 19837–19843. https://doi.org/10.1073/pnas.2009522117
Goldfarb, A., & Tucker, C. (2020). Which Retail Outlets Generate the Most Physical Interactions? (Working Paper No. 27042; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27042
Starnini, M., Aleta, A., Tizzoni, M., & Moreno, Y. (2020). Impact of the accuracy of case-based surveillance data on the estimation of time-varying reproduction numbers. MedRxiv, 2020.06.26.20140871. https://doi.org/10.1101/2020.06.26.20140871
Aiken, E. L., McGough, S. F., Majumder, M. S., Wachtel, G., Nguyen, A. T., Viboud, C., & Santillana, M. (2020). Real-time estimation of disease activity in emerging outbreaks using internet search information. PLOS Computational Biology, 16(8), e1008117. https://doi.org/10.1371/journal.pcbi.1008117
Couture, V., Dingel, J. I., Green, A. E., Handbury, J., & Williams, K. R. (2020). Measuring Movement and Social Contact with Smartphone Data: A Real-Time Application to COVID-19 (Working Paper No. 27560; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27560
Green, J., Edgerton, J., Naftel, D., Shoub, K., & Cranmer, S. J. (2020). Elusive consensus: Polarization in elite communication on the COVID-19 pandemic. Science Advances, eabc2717. https://doi.org/10.1126/sciadv.abc2717
Benton, R. A., Cobb, J. A., & Werner, T. (2020). Firm Partisan Political Positioning and Perceptions of COVID-19-Related Risk [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/tazux
Moreau, D., & Gamble, B. (2020). Conducting a Meta-Analysis in the Age of Open Science: Tools, Tips, and Practical Recommendations [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/t5dwg
Alipio, M. (2020). Do socio-economic indicators associate with COVID-2019 cases? Findings from a Philippine study [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/e2hfa
Children and COVID-19: State-Level Data Report. (n.d.). Retrieved August 12, 2020, from http://services.aap.org/en/pages/2019-novel-coronavirus-covid-19-infections/children-and-covid-19-state-level-data-report/
Mak, H. W., & Fancourt, D. (2020). Predictors of engaging in voluntary work during the Covid-19 pandemic: Analyses of data from 31,890 adults in the UK. https://doi.org/10.31235/osf.io/er8xd
Nguyen, L. H., Drew, D. A., Graham, M. S., Joshi, A. D., Guo, C.-G., Ma, W., Mehta, R. S., Warner, E. T., Sikavi, D. R., Lo, C.-H., Kwon, S., Song, M., Mucci, L. A., Stampfer, M. J., Willett, W. C., Eliassen, A. H., Hart, J. E., Chavarro, J. E., Rich-Edwards, J. W., … Zhang, F. (2020). Risk of COVID-19 among front-line health-care workers and the general community: A prospective cohort study. The Lancet Public Health, 0(0). https://doi.org/10.1016/S2468-2667(20)30164-X
Benitez, J. A., Courtemanche, C. J., & Yelowitz, A. (2020). Racial and Ethnic Disparities in COVID-19: Evidence from Six Large Cities (Working Paper No. 27592; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27592
Fan, Y., Orhun, A. Y., & Turjeman, D. (2020). Heterogeneous Actions, Beliefs, Constraints and Risk Tolerance During the COVID-19 Pandemic (Working Paper No. 27211; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27211
Cronin, C. J., & Evans, W. N. (2020). Private Precaution and Public Restrictions: What Drives Social Distancing and Industry Foot Traffic in the COVID-19 Era? (Working Paper No. 27531; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27531
Sharkey, P., & Wood, G. (2020). The Causal Effect of Social Distancing on the Spread of SARS-CoV-2 [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/hzj7a
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Cluster 0 words: family, home, mother, war, house, dies, Cluster 0 titles: Schindler's List, One Flew Over the Cuckoo's Nest, Gone with the Wind, The Wizard of Oz, Titanic, Forrest Gump, E.T. the Extra-Terrestrial, The Silence of the Lambs, Gandhi, A Streetcar Named Desire, The Best Years of Our Lives, My Fair Lady, Ben-Hur, Doctor Zhivago, The Pianist, The Exorcist, Out of Africa, Good Will Hunting, Terms of Endearment, Giant, The Grapes of Wrath, Close Encounters of the Third Kind, The Graduate, Stagecoach, Wuthering Heights, Cluster 1 words: police, car, killed, murders, driving, house, Cluster 1 titles: Casablanca, Psycho, Sunset Blvd., Vertigo, Chinatown, Amadeus, High Noon, The French Connection, Fargo, Pulp Fiction, The Maltese Falcon, A Clockwork Orange, Double Indemnity, Rebel Without a Cause, The Third Man, North by Northwest, Cluster 2 words: father, new, york, new, brothers, apartments, Cluster 2 titles: The Godfather, Raging Bull, Citizen Kane, The Godfather: Part II, On the Waterfront, 12 Angry Men, Rocky, To Kill a Mockingbird, Braveheart, The Good, the Bad and the Ugly, The Apartment, Goodfellas, City Lights, It Happened One Night, Midnight Cowboy, Mr. Smith Goes to Washington, Rain Man, Annie Hall, Network, Taxi Driver, Rear Window, Cluster 3 words: george, dance, singing, john, love, perform, Cluster 3 titles: West Side Story, Singin' in the Rain, It's a Wonderful Life, Some Like It Hot, The Philadelphia Story, An American in Paris, The King's Speech, A Place in the Sun, Tootsie, Nashville, American Graffiti, Yankee Doodle Dandy, Cluster 4 words: killed, soldiers, captain, men, army, command, Cluster 4 titles: The Shawshank Redemption, Lawrence of Arabia, The Sound of Music, Star Wars, 2001: A Space Odyssey, The Bridge on the River Kwai, Dr. Strangelove or: How I Learned to Stop Worrying and Love the Bomb, Apocalypse Now, The Lord of the Rings: The Return of the King, Gladiator, From Here to Eternity, Saving Private Ryan, Unforgiven, Raiders of the Lost Ark, Patton, Jaws, Butch Cassidy and the Sundance Kid, The Treasure of the Sierra Madre, Platoon, Dances with Wolves, The Deer Hunter, All Quiet on the Western Front, Shane, The Green Mile, The African Queen, Mutiny on the Bounty,
The top IMDB films fit into 2 basic clusters, and 4 main clusters (this project used K-means with a target of 5 but actually clusters 1 and 2 both fit the crime category, and all except Cluster 3 are centred around violence).
If this list is representative of the human psyche we have only 2 basic modes of being: Violence / Musical.
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his dream of it being as easy to “insert facts, data, and models in political discussion as it is to insert emoji” 😉 speaks to a sort of consumerist, on-demand thirst for snippets, rather than a deep understanding of complexity. It’s app-informed, drag-and-drop data for instant government.
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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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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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