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  1. Simulation of Trial Data to Test Speculative Hypotheses about Research Methods.Hamed Tabatabaei Ghomi & Jacob Stegenga - 2023 - In Kristien Hens & Andreas De Block (eds.), Advances in experimental philosophy of medicine. New York: Bloomsbury Academic. pp. 111-128.
    We simulate trial data to test speculative claims about research methods, such as the impact of publication bias.
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  • Is Peer Review a Good Idea?Remco Heesen & Liam Kofi Bright - 2021 - British Journal for the Philosophy of Science 72 (3):635-663.
    Prepublication peer review should be abolished. We consider the effects that such a change will have on the social structure of science, paying particular attention to the changed incentive structure and the likely effects on the behaviour of individual scientists. We evaluate these changes from the perspective of epistemic consequentialism. We find that where the effects of abolishing prepublication peer review can be evaluated with a reasonable level of confidence based on presently available evidence, they are either positive or neutral. (...)
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  • Prediction Markets for Science: Is the Cure Worse than the Disease?Michael Thicke - 2017 - Social Epistemology 31 (5):451-467.
    Prediction markets, which trade contracts based on the results of predictions, have been remarkably successful in predicting the results of political events. A number of proposals have been made to extend prediction markets to scientific questions, and some small-scale science prediction markets have been implemented. Advocates for science prediction markets argue that they could alleviate problems in science such as bias in peer review and epistemically unjustified consensus. I argue that bias in peer review and epistemically unjustified consensuses are genuine (...)
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  • Science, misinformation and digital technology during the Covid-19 pandemic.Aníbal Monasterio Astobiza - 2021 - History and Philosophy of the Life Sciences 43 (2):1-6.
    Three interdependent factors are behind the current Covid-19 pandemic distorted narrative: (1) science´s culture of “publish or perish”, (2) misinformation spread by traditional media and social digital media and (3) distrust of technology for tracing contacts and its privacy-related issues. In this short paper, I wish to tackle how these three factors have added up to give rise to a negative public understanding of science in times of a health crisis, such as the current Covid-19 pandemic and finally, how to (...)
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