Crowdsourcing hypothesis tests: Making transparent how design choices shape research results

To what extent are research results influenced by subjective decisions that scientists make as they design studies? Fifteen research teams independently designed studies to answer fiveoriginal research questions related to moral judgments, negotiations, and implicit cognition. Participants from two separate large samples (total N > 15,000) were then randomly assigned to complete one version of each study. Effect sizes varied dramatically across different sets of materials designed to test the same hypothesis: materials from different teams renderedstatistically significant effects in opposite directions for four out of five hypotheses, with the narrowest range in estimates being d = -0.37 to +0.26. Meta-analysis and a Bayesian perspective on the results revealed overall support for two hypotheses, and a lack of support for three hypotheses. Overall, practically none of the variability in effect sizes was attributable to the skill of the research team in designing materials, while considerable variability was attributable to the hypothesis being tested. In a forecasting survey, predictions of other scientists were significantly correlated with study results, both across and within hypotheses. Crowdsourced testing of research hypotheses helps reveal the true consistency of empirical support for a scientific claim.</div

Emotional Congruence and Judgments of Honesty and Bias

Psychological and philosophical discussions typically understand honesty as reporting truth with propositional statements. In this model, emotions are often seen as irrelevant or a hindrance to honesty, because they can bias our reports. In relational contexts, however, emotions can provide information about deep-seated convictions. We report the results of a study (N = 827) finding that individuals whose emotional responses are congruent with their explicitly stated egalitarian positions are judged as significantly more honest and less prejudiced than those with incongruent emotional responses. This is seen in judgments of white male targets who have negative emotional responses to a black man, a gay man, and a female supervisor. These results suggest that emotional reactions provide information used when judging the honesty and bias of an individual

Psychological Aspects of Food Biodesign

In light of what is known of the cognitive, social, developmental, and evolutionary psychology of human food choice, the anxiety and resistance prompted by genetically modified (GM) foods is unsurprising. The underlying psychological mechanisms that govern food preferences suggest why GM foods have become so controversial so easily. Views of government regulation and business practices also play a role in the public reaction to GM foods

Deep multiple instance learning for foreground speech localization in ambient audio from wearable devices

Over the recent years, machine learning techniques have been employed to produce state-of-the-art results in several audio related tasks. The success of these approaches has been largely due to access to large amounts of open-source datasets and enhancement of computational resources. However, a shortcoming of these methods is that they often fail to generalize well to tasks from real life scenarios, due to domain mismatch. One such task is foreground speech detection from wearable audio devices. Several interfering factors such as dynamically varying environmental conditions, including background speakers, TV, or radio audio, render foreground speech detection to be a challenging task. Moreover, obtaining precise moment-to-moment annotations of audio streams for analysis and model training is also time-consuming and costly. In this work, we use multiple instance learning (MIL) to facilitate development of such models using annotations available at a lower time-resolution (coarsely labeled). We show how MIL can be applied to localize foreground speech in coarsely labeled audio and show both bag-level and instance-level results. We also study different pooling methods and how they can be adapted to densely distributed events as observed in our application. Finally, we show improvements using speech activity detection embeddings as features for foreground detection. © 2021, The Author(s).National Institutes of HealthOpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

‘Personality in Its Natural Habitat’ Revisited: A Pooled, Multi‐sample Examination of the Relationships Between the Big Five Personality Traits and Daily Behaviour and Language Use

Past research using the Electronically Activated Recorder (EAR), an observational ambulatory assessment method for the real-world measurement of daily behaviour, has identified several behavioural manifestations of the Big Five domains in a small college sample (N = 96). With the use of a larger and more diverse sample of pooled data from N = 462 participants from a total of four community samples who wore the EAR from 2 to 6 days, the primary purpose of the present study was to obtain more precise and generalizable effect estimates of the Big Five-behaviour relationships and to re-examine the degree to which these relationships are gender specific. In an extension of the original article, the secondary purpose of the present study was to examine if the Big Five-behaviour relationships differed across two facets of each Big Five domain. Overall, while several of the behavioural manifestations of the Big Five were generally consistent with the trait definitions (replicating some findings from the original article), we found little evidence of gender differences (not replicating a basic finding from the original article). Unique to the present study, the Big Five-behaviour relationships were not always comparable across the two facets of each Big Five domain. (C) 2020 European Association of Personality Psychology12 month embargo; published online: 16 July 2020This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Loneliness and time alone in everyday life: A descriptive-exploratory study of subjective and objective social isolation

Loneliness—the subjective experience of social isolation—is a common experience that can become an enduring feature of everyday life. How does feeling lonely relate to spending time alone? In this descriptive-exploratory study, we used the Electronically Activated Recorder (EAR), a naturalistic observation tool that samples sounds from participants’ daily lives, to assess time spent alone as an index of social isolation. We combined data from three samples (N = 426) to examine the association between subjective and objectively-assessed isolation, and whether the association varies as a function of gender, marital status, and age. The constructs are weakly but significantly correlated, and spending more than 75% of time alone was associated with much higher loneliness scores, especially among older adults.Open access articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]