- "Girls’ comparative advantage in reading can largely explain the gender gap in math-related fields" by Breda and Napp (2019), PNAS. Very interesting paper that the difference in reading abilities between boys and girls in early age can explain the gender gap in math-career and intentions. I am not 100% sure what is policy implication given the complexity of the issue e.g. family planning, but authors argue "to better inform students regarding the returns to different fields of study, something that is likely to trigger large effects on educational choices". Indeed, informational treatment can improve job prospects in general population and Breda et al. (2018) show that in girls. However, do we improve them or bias?
- "A project-management tool from the tech industry could benefit your lab" by David Adam (2019), Nature. A friend of mine pointed out to me a "Scrum" as useful tool to for project management used in the industry. It is interesting to see that advocates of this approach in science.
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Reporting errors and biases in published empirical findings: Evidence from innovation research6/8/2019 Highlights
Abstract: Errors and biases in published results compromise the reliability of empirical research, posing threats to the cumulative research process and to evidence-based decision making. We provide evidence on reporting errors and biases in innovation research. We find that 45% of the articles in our sample contain at least one result for which the provided statistical information is not consistent with reported significance levels. In 25% of the articles, at least one strong reporting error is diagnosed where a statistically non-significant finding becomes significant or vice versa using the common significance threshold of 0.1. The error rate at the test level is very small with 4.0% exhibiting any error and 1.4% showing strong errors. We also find systematically more marginally significant findings compared to marginally non-significant findings at the 0.05 and 0.1 thresholds of statistical significance. These discontinuities indicate the presence of reporting biases. Explorative analysis suggests that discontinuities are related to authors’ affiliations and to a lesser extent the article’s rank in the issue and the style of reporting.
Read more... "How might a government encourage more opportunity-led entrepreneurship and science-led innovation careers at a large scale? This question was the starting point that led us to begin some research to consider why the youth are not choosing these careers. Perhaps young people not have relevant skills and knowledge? However, it seems that even if young people do have the right skills, they might not believe they can choose these career paths." Read more on IGL website. |
About this BlogI would like to share some random thoughts on the research topics that I find interesting and my research activity. Archives
September 2019
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