"Growing Citizens: An Interdisciplinary Reflection on Citizenship Education" by Alison Elliot & Heidi Poon

Review ofAlison Elliot & Heidi Poon, Growing Citizens: An Interdisciplinary Reflection on Citizenship Education (Edinburgh: Saint Andrew Press, 2009

Affinity Precipitation of Active Rho-GEFs Using a GST-tagged Mutant Rho Protein (GST-RhoA(G17A)) from Epithelial Cell Lysates

Proteins of the Rho family of small GTPases are central regulators of the cytoskeleton, and control a large variety of cellular processes, including cell migration, gene expression, cell cycle progression and cell adhesion 1. Rho proteins are molecular switches that are active in GTP-bound and inactive in GDP-bound state. Their activation is mediated by a family of Guanine-nucleotide Exchange Factor (GEF) proteins. Rho-GEFs constitute a large family, with overlapping specificities 2. Although a lot of progress has been made in identifying the GEFs activated by specific signals, there are still many questions remaining regarding the pathway-specific regulation of these proteins. The number of Rho-GEFs exceeds 70, and each cell expresses more than one GEF protein. In addition, many of these proteins activate not only Rho, but other members of the family, contributing further to the complexity of the regulatory networks. Importantly, exploring how GEFs are regulated requires a method to follow the active pool of individual GEFs in cells activated by different stimuli. Here we provide a step-by-step protocol for a method used to assess and quantify the available active Rho-specific GEFs using an affinity precipitation assay. This assay was developed a few years ago in the Burridge lab 3,4 and we have used it in kidney tubular cell lines 5,6,7. The assay takes advantage of a "nucleotide free" mutant RhoA, with a high affinity for active GEFs. The mutation (G17A) renders the protein unable to bind GDP or GTP and this state mimics the intermediate state that is bound to the GEF. A GST-tagged version of this mutant protein is expressed and purified from E. coli, bound to glutathione sepharose beads and used to precipitate active GEFs from lysates of untreated and stimulated cells. As most GEFs are activated via posttranslational modifications or release from inhibitory bindings, their active state is preserved in cell lysates, and they can be detected by this assay8. Captured proteins can be probed for known GEFs by detection with specific antibodies using Western blotting, or analyzed by Mass Spectrometry to identify unknown GEFs activated by certain stimuli

Quantifying Support for the Null Hypothesis in Psychology: An Empirical Investigation

In the traditional statistical framework, nonsignificant results leave researchers in a state of suspended disbelief. In this study, we examined, empirically, the treatment and evidential impact of nonsignificant results. Our specific goals were twofold: to explore how psychologists interpret and communicate nonsignificant results and to assess how much these results constitute evidence in favor of the null hypothesis. First, we examined all nonsignificant findings mentioned in the abstracts of the 2015 volumes of Psychonomic Bulletin & Review, Journal of Experimental Psychology: General, and Psychological Science (N = 137). In 72% of these cases, nonsignificant results were misinterpreted, in that the authors inferred that the effect was absent. Second, a Bayes factor reanalysis revealed that fewer than 5% of the nonsignificant findings provided strong evidence (i.e., BF01 > 10) in favor of the null hypothesis over the alternative hypothesis. We recommend that researchers expand their statistical tool kit in order to correctly interpret nonsignificant results and to be able to evaluate the evidence for and against the null hypothesis

A Consensus-Based Transparency Checklist

We present a consensus-based checklist to improve and document the transparency of research reports in social and behavioural research. An accompanying online application allows users to complete the form and generate a report that they can submit with their manuscript or post to a public repository

Author Correction: A consensus-based transparency checklist.

An amendment to this paper has been published and can be accessed via a link at the top of the paper

Inequality in researchers’ minds: Four guiding questions for studying subjective perceptions of economic inequality

This is the final version. Available on open access from Wiley via the DOI in this recordSubjective perceptions of inequality can substantially influence policy attitudes, public health metrics, and societal well-being, but the lack of consensus in the scientific community on how to best operationalize and measure these perceptions may impede progress on the topic. Here, we provide a theoretical framework for the study of subjective perceptions of inequality, which brings critical differences to light. This framework—which we conceptualize as a series of four guiding questions for studying subjective perceptions of economic inequality—serves as a blueprint for the theoretical and empirical decisions researchers need to address in the study of when, how, and why subjective perceptions of inequality are consequential for individuals, groups, and societies. To lay the foundation for a comprehensive approach to the topic, we offer four theoretical and empirical decisions in studying subjective perceptions of inequality, urging researchers to specify: (1) What kind of inequality? (2) What level of analysis? (3) What part of the distribution? and (4) What comparison group? We subsequently discuss how this framework can be used to organize existing research and highlight its utility in guiding future research across the social sciences in both the theory and measurement of subjective perceptions of inequality.Tobin FoundationInternational Association for Research in Economic Psychology (IAREP)Department of Economics, University of Exeter Business Schoo

Contextual factors predicting compliance behavior during the COVID-19 pandemic: A machine learning analysis on survey data from 16 countries

Voluntary isolation is one of the most effective methods for individuals to help prevent the transmission of diseases such as COVID-19. Understanding why people leave their homes when advised not to do so and identifying what contextual factors predict this non-compliant behavior is essential for policymakers and public health officials. To provide insight on these factors, we collected data from 42,169 individuals across 16 countries. Participants responded to items inquiring about their socio-cultural environment, such as the adherence of fellow citizens, as well as their mental states, such as their level of loneliness and boredom. We trained random forest models to predict whether someone had left their home during a one-week period during which they were asked to voluntarily isolate themselves. The analyses indicated that overall, an increase in the feeling of being caged leads to an increased probability of leaving home. In addition, an increased feeling of responsibility and an increased fear of getting infected decreased the probability of leaving home. The models predicted compliance behavior with between 54% and 91% accuracy within each country’s sample. In addition, we modeled factors leading to risky behavior in the pandemic context. We observed an increased probability of visiting risky places as both the anticipated number of people and the importance of the activity increased. Conversely, the probability of visiting risky places increased as the perceived putative effectiveness of social distancing decreased. The variance explained in our models predicting risk ranged from < .01 to .54 by country. Together, our findings can inform behavioral interventions to increase adherence to lockdown recommendations in pandemic conditions.info:eu-repo/semantics/publishedVersio