Comment in 2020

The harassment of researchers working in the social sciences—not rarely an organized effort targeting members of marginalized groups—is most alarming. Its implications reach from severe personal consequences to the risk of scientific self-censorship. We invite readers to engage in a much-needed discourse about this worrisome phenomenon.

The year 2020 has been marked by unprecedented cascading traumas, including the COVID-19 pandemic, an economic recession, race-driven social unrest and weather-related disasters. Mental health consequences of direct and media-based exposure to compounding stressors may be profound. Policymakers must act to ease the burden of trauma to protect public health.

Social and behavioural scientists have attempted to speak to the COVID-19 crisis. But is behavioural research on COVID-19 suitable for making policy decisions? We offer a taxonomy that lets our science advance in ‘evidence readiness levels’ to be suitable for policy. We caution practitioners to take extreme care translating our findings to applications.

Twitter announced on 18 June 2019 that it would remove the precise geotagging feature in tweets. In addition to protecting the location privacy of users, this change also affects human behaviour studies based on geotagged tweets. We discuss the potential impact of Twitter’s decision and how researchers can respond to this change.

The impact of pandemics is magnified by the coexistence of two contradicting reactions to rare dire risks: panic and the ‘it won’t happen to me’ effect that hastens spread of the disease. We review research that clarifies the conditions that trigger the two biases, and we highlight the potential of gentle rule enforcement policies that can address these problematic conditions.

COVID-19 has not affected all scientists equally. A survey of principal investigators indicates that female scientists, those in the ‘bench sciences’ and, especially, scientists with young children experienced a substantial decline in time devoted to research. This could have important short- and longer-term effects on their careers, which institution leaders and funders need to address carefully.

Bias and racism in the biomedical community thwart scientific advancement, reduce the pipeline of diverse clinicians and scientists, and contribute to racial and ethnic health disparities. We advocate for proactive antiracism approaches to eliminate barriers impacting people of colour, promote equity and achieve a more effective biomedical community.

Do purchasable randomised reward mechanisms in video games (loot boxes) constitute gambling? Opinions often rest on whether virtual items obtained from loot boxes have real-world value. Using market data from real transactions, we show that virtual items have real-world monetary value and therefore could be regulated under existing gambling legislation.

The scientific community’s response to COVID-19 has resulted in a large volume of research moving through the publication pipeline at extraordinary speed, with a median time from receipt to acceptance of 6 days for journal articles. Although the nature of this emergency warrants accelerated publishing, measures are required to safeguard the integrity of scientific evidence.

Most people in the Western, developed world prefer natural things, especially foods. We posit that there is neither theoretical nor empirical support for the widespread beliefs about the superiority of natural entities with respect to human welfare. Nature is not particularly benevolent.

Prereg posters are conference posters that present planned scientific projects. We provide preliminary evidence for their value in receiving constructive feedback, promoting open science and supporting early-career researchers.

Selfless motivations for charitable giving are often represented as being superior to selfish ones. But, we argue, evidence from the behavioural sciences suggests that such a ‘hierarchy of charity’ may stand in the way of what ultimately matters: generating the most impactful giving overall.

The debate over whether autocracies or democracies are better at fighting epidemics is misguided. Under President Xi Jinping’s centralized command, his administration has both succeeded and failed at handling the COVID-19 crisis. While it effectively curbed infections within China after the virus had spread, it failed to stem the outbreak before it went global.

Why is there no consensual way of conducting Bayesian analyses? We present a summary of agreements and disagreements of the authors on several discussion points regarding Bayesian inference. We also provide a thinking guideline to assist researchers in conducting Bayesian inference in the social and behavioural sciences.

The behavioral sciences underestimate the uncertainty of research findings and thus overestimate replicability. Metrologists in the physical sciences quantify all material components of uncertainty, even if some components must be quantified using non-statistical means. Behavioral science should follow suit.