What Can Stop Bad Science? Open Science and Modified Funding Lotteries

[From the working paper, “Open science and modified funding lotteries can impede the natural selection of bad science” By Paul Smaldino, Matthew Turner, and Pablo Contreras Kallens, posted at OSF Preprints]
“…we investigate the influence of three key factors on the natural selection of bad science: publication of negative results, improved peer review, and criteria for funding allocation.”
“…our results indicate that funding agencies have the potential to play an outsized role in the improvement of science by promoting research that passes tests for rigor. Such tests include commitments to open data and open code (which permit closer scrutiny), preregistration and registered reports, and research programs with strong theoretical bases for their hypotheses. Wide-scale adoption of these and similar criteria for funding agencies can, in theory, have substantial long-term effects on reducing the rates of false discoveries.”
“Our results also highlight the contribution of open science practices. Improving peer review and reducing publication bias led to improvements in the replicability of published findings in our simulations. Alone, each of these open science improvements required extremely high levels of implementation to be effective.”
“Fortunately, we also found that the two factors could work in tandem to improve the replicability of the published literature at lower, though still high, levels of efficacy.”
“… in the absence of specific incentives at the funding or hiring level for methodological rigor, open science improvements are probably not sufficient to stop the widespread propagation of inferior research methods, despite the optimism that often surrounds their adoption.”
To read the paper, click here

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