A little knowledge is a dangerous thing: excess confidence explains negative attitudes towards science

Scientific knowledge has been accepted as the main driver of development, allowing for longer, healthier, and more comfortable lives. Still, public support to scientific research is wavering, with large numbers of people being uninterested or even hostile towards science. This is having serious social consequences, from the anti-vaccination community to the recent "post-truth" movement. Such lack of trust and appreciation for science was first justified as lack of knowledge, leading to the "Deficit Model" \cite{Durant:1989, Bauer:2007}. As an increase in scientific information did not necessarily lead to a greater appreciation, this model was largely rejected, giving rise to "Public Engagement Models" \cite{Miller:2001}. These try to offer more nuanced, two-way, communication pipelines between experts and the general public, strongly respecting non-expert knowledge, possibly even leading to an undervaluing of science. Therefore, we still lack an encompassing theory that can explain public understanding of science, allowing for more targeted and informed approaches. Here, we use a large dataset from the Science and Technology Eurobarometer surveys, over 25 years in 34 countries \cite{Bauer:2012}, and find evidence that a combination of confidence and knowledge is a good predictor of attitudes towards science. This is contrary to current views, that place knowledge as secondary, and in line with findings in behavioral psychology, particularly the Dunning-Kruger effect, as negative attitudes peak at intermediate levels of knowledge, where confidence is largest. We propose a new model, based on the superposition of the Deficit and Dunning-Kruger models and discuss how this can inform science communication.Comment: 9 pages, 3 figures, 1 table; Appendix with 12 pages, 9 figures, 8 table

Increasing returns to scale and international diffusion of technology: an empirical study for Brazil (1976-2000)

This article aims at exploring the empirical evidence regarding the effects of increasing returns to scale and international technological diffusion on the Brazilian manufacturing industry. Our departure point is a Kaldorian-type theoretical model that provides not only the positive effects of scale but also of diffusion on industrial performance. We use Vector Auto Regressive (VAR) for testing the model. VAR will estimate the coefficients related to industrial output, labor productivity, exports and the technological gap between the United States and Brazil. This technique also provides simulations for the short-term and long-term trajectories under exogenous shocks. The observations are on a three-month period basis and the sampling period runs from the second half of 1976 to the second half of 2000. The conclusion highlights both evidences of increasing returns on the Brazilian industry that faces, however, some structural constraints. Besides, the model also reveals Brazil's difficulties to catch uptechnological gap; increasing returns to scale; economic growth; Brazil