1/6 I think that a #DeSci economy that covers all aspects of #academia in one ecosystem (#publications, #peerreview, and #funding) is more valuable and more likely to succeed in the long run than a project that covers only one or two of these aspects. Why? ...
2/6 Because of #networkeffects. All three parts of academia co-depend and influence each other. There are positive network externalities to solving problems in publishing, peer review, and funding to other parts of #academia. ...
3/6 And if such an integrated #DeSci solution helps to reward #scientists more fairly, solve their #funding problems, and raise the standards of #peerreview and #publications, every #scientist would want to be a part of it. ...
4/6 And this would create the biggest #networkeffect of them all - a place where the best scientists of all disciplines from all countries would come together: The ultimate brain power engine for break-through #innovations. ...
5/6 And that would not only be nice for non-profit #funders of #Science, it would also be the ideal place for R&D-intense businesses to outsource a part of their #RandD. Think #replication studies for industry-relevant publications or business-science collaborations at scale. ...
6/6 That's what we're planning to build at @DesciLabs. It's a dauntingly complex task, but it's doable and the rewards for #Science, #business, and #society are huge.

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More from @PKoellinger

Sep 1, 2020
1/25 New paper out from my group on the role of genetic luck on education, income, and health! FAQ at bit.ly/3f5TXoV. We investigate the consequences of random genetic differences between siblings in their predisposition for high income... tinbergen.nl/discussion-pap…
2/25 and find that the siblings who "won" the genetic lottery by having a (slightly) higher polygenic score (PGS) for income tend to have more favourable outcomes throughout life, including a higher chance to get a college degree, a better job, living in a better neighbourhood...
3/25 and better health outcomes later in life. The figure below plots the OLS regression coefficients for the standardized income PGS with 95% confidence intervals. Upper panel - percentage scale, lower panel - standardized betas, asterisks for p<0.05 corrected for multiple tests
Read 25 tweets
May 6, 2020
1/16 As an economist, I keep asking myself: How bad is #COVID19, who's at risk, and what's the right policy to deal with this? Here are some insights from a pretty amazing, harmonized dataset on overall mortality from 24 European countries up to week 18: euromomo.eu/graphs-and-map…
2/16 Let's look at the trend in mortality over the last few years. I'm showing Z-scores here for comparability across countries: 0 means average mortality, values between -2 and 2 are roughly the 95% confidence interval around the average and >2 means significantly more deaths.
3/16 First insight: Mortality in Europe goes up every winter, partly as a result of the annual flu wave. 2020 started off great, but then mortality exploded in March-April, just when #COVID19 hit Europe and many countries responded with drastic measures to slow down infections.
Read 16 tweets
Apr 25, 2020
1/4 Interesting: A wet lab study from Germany suggests that some degree of limited background immunity against #COVID19 may exist in the population (~1/3 of their healthy donor sample) due to previous infections with other "common cold" coronaviruses.
bit.ly/3cKIyJE
2/4 The study hypothesizes that this may be a factor related to severity of SARS-CoV-2 infections and may help to explain the high prevalence of nonsymptomatic or mild infections among younger people and kids (because they get a "common cold" more often).
3/4 The study calls for more data to understand cross-reactive (partial) immunity across coronaviruses better -> important for risk evaluation, patient monitoring, vaccine development, and better, more efficient strategies to combat #Covid19.
Read 4 tweets
Apr 13, 2020
Thread: 1/ An interdisciplinary group of scientists from the German National Academy of Sciences (@Leopoldina) has released a consensus document with recommendations about how to manage the next phases of the #Covid19 pandemic... bit.ly/2Ruiavt
2/ They recommend a stepwise relaxation of the current lockdown measures ASAP, with the goal to return to normality while simultaneously keeping the number of new infections low & without overwhelming the capacity of the health care system...
3/ The report emphasizes the importance of a more intelligent, targeted management of the pandemic. Key elements are: (i) more testing of infections and immunity (ii) targeted isolation (iii) the need for large, longitudinal, rep pop samples to fine-tune models & policy...
Read 13 tweets

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