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"You're a Nobody When you're Unemployed": Exploring the Content of Unemployed People's Stereotype
No full textUnemployed people bear a stigma that builds on the stereotype of "the unemployed" and is associated with many adverse outcomes. No study has used the dimensions and facets of the latest integrated stereotype framework to describe their stereotype and compare it with other groups. In Study 1 among university students (n = 241), we show that unemployed people are rated lower than employed people on the horizontal and the vertical dimensions of their stereotypes, as well as on the facets of capacity, assertiveness, morality and friendliness. We show that unemployed people are also rated the lowest when compared to a high-high occupation (firefighters) and a low-low occupation (railroad workers). In Study 2, we replicate these findings with university students (n = 193) and show that unemployed people are also blatantly dehumanized when compared to the same targets. In Study 3, we show that vocational integration workers (n = 123) also rate unemployed people lower than employed people on both dimensions and facets, but not on morality. Overall, we conclude that unemployed people have a highly destructive stereotype that is lacking in every dimension and facet, and that they are overly despised
Corpora for Polarisation Issues in Social Media
No full textWith the use of computational methods, our corpora allows an investigation of recurring patterns in polarising exchanges across topics of discussion and media platforms, and conduct both quantitative and qualitative analyses of language structures leading to and engaged in polarisation. For further details see our paper:
Ewelina Gajewska, Katarzyna Budzynska, Barbara Konat, Marcin Koszowy, Konrad Kiljan, Maciej Uberna, He Zhang (2024) Ethos and Pathos in Online Group Discussions: Corpora for Polarisation Issues in Social Media., arXiv preprint, arXiv:2404.04889, DOI 10.48550/arXiv.2404.04889.
The work reported in this paper was supported in part by CHIST-ERA under grant 2022/04/Y/ST6/00001, in part by the Polish National Science Centre (NCN) under grant 2020/39/I/HS1/02861, in part by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 860621, and in part by VW foundation (VolkswagenStiftung) under grant 98 542
Brief Speech Samples Reveal Emotional States in Daily Life
No full textDoes our speech – what we say and how we say it – reveal information about our emotional experiences? Scholars have long made assumptions about such links but most evidence is derived from emotion expressions in controlled laboratory work, with only limited studies of emotional experience in naturalistic settings. Using both modern foundation models and traditional speech analysis methods (LIWC and prosodic descriptors), we tested whether brief, prompted speech samples recorded via smartphones could predict concurrent, self-reported emotional states in daily life (N = 934 participants; 12,285 observations). Cross-validated models showed that speech samples predict emotional states (contentment: r_md = .37; sadness: r_md = .23; arousal: r_md = .34), with spoken content captured by foundation-model text embeddings revealing the strongest emotional signal. The findings offer insights into the linguistic characteristics of naturalistic emotional speech, with implications for scalable emotion inference via speech in daily life
Personalized neural state segmentation: validating the GSBS algorithm for individual-level fMRI data
No full textHumans segment experience into a nested series of discrete events, separated by neural state transitions that can be identified in fMRI data collected during passive movie viewing. Current neural state segmentation techniques manage the noisiness of fMRI data by modelling groups of participants at once. However, the perception of event boundaries is itself idiosyncratic. As such, we developed a novel denoising pipeline to separate meaningful signal from noise and validated the Greedy State Boundary Search (GSBS) algorithm for use in individual participants. We applied the GSBS to publicly available (1) young adult (YA) and (2) developmental fMRI datasets. After extensive denoising, we confirmed that personalized YA neural state transitions exhibited a canonical temporal cortical hierarchy and were related to normative behavioural boundaries across time in key regions such as the posterior parietal cortex. Further, we used machine learning to show that the strongest neural transitions could be used to predict the timing of normative boundary judgements. Results from the developmental dataset also demonstrated important boundary conditions for estimating personalized neural state transitions. Nonetheless, some brain-behaviour relations were still apparent in individually modelled developmental data. These validations pave the way for applying personalized fMRI modelling to the study of event segmentation; what meaningful insights could we be missing when we average away what makes each of us unique
Perceived control as a resilience factor: Associations with neural, physiological and affective stress responses and mental health
No full textThis project contains analysis code and data associated with the manuscript "Perceived control as a resilience factor: Influences on neural, physiological and affective stress responses and mental health", available as a preprint here: https://osf.io/preprints/osf/szpa
Classifying Eating Styles Based on Appetitive and Impulsive Traits
No full textThis project is aimed at (1) investigating the structure of eating style in a large non-clinical adult sample and (2) comparing the fit of categorical, dimensional, and hybrid categorical-dimensional models of eating style, based on co-occurring appetitive and impulsive traits
Modifiable Protective Factors that Promote Resilience in Trauma-Exposed Adults
No full textThis systematic review examines the modifiable protective factors that promote resilience in adults who have experienced Criterion A events. The review seeks to explore the protective factors enhancing resilience at the individual (micro), community (mezzo), and policy levels (macro). By identifying modifiable protective factors that contribute to well-being, the review emphasizes a strengths-based approach to trauma recovery, considering modifiable behavioral interventions between biological, psychological, social, and cultural factors
Beyond the Mean: How Thinking About The Distribution of Public Opinions Reduces Politicians' Perceptual Errors
No full textRecent studies find that elected politicians regularly over-estimate the conservatism of their constituents’ preferences. While these findings have potentially concern- ing implications for democratic representation, they depend on the magnitude and sources of this ‘conservative over-estimation,’ neither of which is well-understood. Here, we show that a novel approach to measuring politicians’ perceptions—whereby politicians draw the distribution of their constituents’ positions, rather than pro- vide a point estimate—clarifies the magnitude and sources of politicians’ perceptual errors. While the vast majority of politicians in our sample exhibit a conservative bias, our ‘perceived-distribution’ task cuts the size of this bias in half. Exploring how politicians build out public-opinion distributions, we further show that conser- vative over-estimation is counterbalanced by projection effects among politicians on the left, but that projection among politicians on the right reinforces it. Our re- sults raise questions about existing accounts of elite misperception and help identify cognitive sources of the conservative over-estimation