PAPER PEOPLE AND DIGITAL MEMORY: RECREATING THE PUBLIC AND PRIVATE IN JAPAN

This research examines how reading and writing on digital platforms establishes public and private spheres in Tokyo, Japan. Based upon findings from a group of students at an international University, I develop new modes of thinking about people and their use of Internet capable devices by exploring the paradoxes present in contemporary literacies. Contextualizing reading and writing within the speech patterns and exchange rituals (aisatsu) which mark public spheres in Japan, writing practices are found to reflect multiple nuanced identity performances in which the varied use of the cultural principles uchi/soto (inside/outside) and ura/omote (back/front) create parallel publics. Constructed by authors and recognized by readers, these parallel publics are the result of student agency as well as the materiality of platform programing and device capabilities. Contemporary literacies have developed conventions which account for the message recipient carrying an ever-present Internet capable device, leading authors to utilize message practices which align the proximity of a platform to levels of intimacy in a relationship. Authors also compose messages which are less likely to require the receiver to excuse themselves from any given social situation. The ubiquity of human-device pairs has also impacted memory practices, with youths prioritizing recognition skills over memorization

Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology

Gould E, Fraser H, Parker T, et al. Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology. 2023.Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different (mostly social science) fields, and has found substantial variability among results, despite analysts having the same data and research question. We implemented an analogous study in ecology and evolutionary biology, fields in which there have been no empirical exploration of the variation in effect sizes or model predictions generated by the analytical decisions of different researchers. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment), and the project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future