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Dancing on the edge?
(2025)
Objective
Although recreational use of gamma-hydroxybutyrate (GHB) and its precursors gamma-butyrolactone (GBL) and 1,4-butanediol (BD) is increasing and poses high risks (e.g. overdose, addiction, withdrawal), research on motives driving their use is lacking. The present study therefore aims to systematically examine the underlying motives and associations with psychological distress.
Method
This mixed-methods longitudinal study includes two waves of anonymous online data collection (11/2022–01/2023; 11/2023–01/2024) in Germany. The adult sample (Nbaseline = 2196; with nfollow-up = 240) was recruited via convenience-sampling, primarily from Berlin’s nightlife-scene, and comprises GHB/GBL/BD users and their non-using peers. Structured motive ratings and open-ended self-reported motives were analyzed quantitatively and qualitatively. Cross-lagged panel-models were used to test bidirectional longitudinal associations between GHB/GBL/BD use and anxiety and depressive symptoms, while moderation analyses were used to assess whether coping motives influenced these relationships.
Results
GHB/GBL/BD use was primarily driven by hedonistic motives such as euphoria and sexual stimulation, while coping-related motives (e.g. anxiety reduction, mood improvement) were also endorsed, particularly among heavy users. Motives remained largely stable over time. Anxiety and depressive symptoms did not predict later use, nor vice versa. However, coping motives moderated the relationship, strengthening the association between symptoms and use frequency.
Conclusions
While GHB/GBL/BD are mainly used for recreational hedonistic purposes, distress-related motives also seem to play a role, especially in heavier use. These findings highlight the need for targeted prevention, harm-reduction, and therapeutic strategies that consider both hedonistic and coping-driven use, while accounting for the unique characteristics and risks associated with GHB/GBL/BD.
From evidence to testimony
(2026)
The essay looks closely at Exhibit A-i: The Refugee Account (2023), a collaborative human rights project communicating the experience of 32 refugees detained by the Australian government in offshore processing centers under inhumane conditions. To make up for the lack of images, they used the AI-powered text-image generator Midjourney. Analyzing the project, I am interested in how to conceptually approach these images that refer to the history and theory of photography but do not share photography’s ontology. Drawing both on traditional photo theory and memory studies as well as literature dealing with algorithmic images, I make an argument for these images to constitute a new kind of testimony, where individual memory and collective image archive intersect. To do so, I draw on select modes of production of AI-generated images, detailing aspects such as the linking of text and image as well as the reliance on noise to make a representation. While acknowledging the power asymmetries between the Global North and Global South inherent to AI, I argue that projects such as Exhibit A-i can appropriate the technology to question its use in migration policies, all the while demanding from the audience to reflect on its own implication.
Background
There is accumulating evidence suggesting that spatial language skills are associated with early numerical development (i.e., verbal number skills and numerical magnitude understanding). However, intervention studies allowing for a causal interpretation of this association are largely missing.
Aims
Therefore, we aimed at investigating the effects of training children's spatial language skills on the development of basic numerical skills.
Sample
The intervention group comprised n = 54 and the non-trained control group n = 72 4-6-year-old children (Mage = 60.58 months).
Methods
In a pre-post-test control group design small groups of four to eight children were trained six times (mostly twice a week) for about 20 min each. The training focused on production and comprehension of the spatial terms in front of, behind, to the left, and to the right with effects on numerical magnitude understanding and verbal number skills being evaluated.
Results
Comparing training and control group on performance gains between pre- and post-test revealed significantly higher gains for the intervention group in spatial language production and comprehension as well as numerical magnitude understanding, but not verbal number skills.
Conclusion
These findings provide first evidence for a causal link between children's spatial language skills and the development of their numerical magnitude understanding. This highlights the relevance of mastering specific spatial language terms for children's early numerical development.
Studien zeigen, dass es frühpädagogischen Fachkräften nicht umfassend gelingt, Kindern in Alltagssituationen Beteiligungsmöglichkeiten zu gewähren (Hildebrandt et al., 2021). Es fehlen allerdings Forschungsergebnisse zur Frage, welche Faktoren diese beeinflussen. Es gibt Hinweise, dass insbesondere Orientierungen einen Einfluss auf pädagogisches Handeln haben (Fröhlich-Gildhoff et al., 2011). Daher wurde eine Interviewstudie mit der Frage durchgeführt, welchen Orientierungen pädagogische Fachkräfte bezüglich partizipativen Handelns mit Kindern nachgehen und welches Rollenverständnis sie diesbezüglich haben. Es wurde untersucht, welche Aspekte die Orientierungen und das Rollenverständnis bezüglich Partizipation beeinflussen. Zentrales Ergebnis der Studie ist, dass die durch das Team initiierte und von einer offenen, wertschätzenden Teamkultur getragene Selbstreflexion über (berufs-)biografische Erlebnisse eine maßgebliche Rolle für die Bereitschaft spielt, partizipative Bildungsprozesse zu gestalten. Einrichtungsleitungen und Trägern kommt dabei die Verantwortung zu, entsprechende Ressourcen im Team zur Verfügung zu stellen.
In this study, we investigate with the Discrete Element Method (DEM) the mechanical behavior of a cohesionless granular material under undrained true triaxial conditions, considering both monotonic and cyclic loading. We link the microstructure evolution within the granular assembly to its macroscopic cyclic response. To capture the mechanical response of our reference material (Karlsruhe fine sand), a rolling resistance linear contact model along with spherical particles is calibrated through a trial-and-error process, adjusting the model parameters to capture the experimentally observed behavior as close as possible. A series of cyclic undrained triaxial tests were simulated to investigate the micromechanical processes underlying liquefaction of sand under cyclic shearing. We analyzed the evolution of various fabric indices, including the redundancy index, contact normal orientations, and fabric anisotropy in relation to the pre- and post-liquefaction responses. The results reveal that a redundancy index below unity provides a unified criterion for the loss of the isostatic condition within the granular assembly, which triggers the onset of liquefaction. Throughout the cyclic loading process, sliding-dominant contact-yielding mechanisms remain prevalent. Additionally, significant changes in contact normal orientation and increasing fabric anisotropy dependent on the induced axial strain occur as the sample undergoes post-liquefaction deformation.
The affective connotations of words are central to meaning and important predictors of many social processes. As such, understanding the degree to which commercially-available generative language models (LLMs) replicate human judgements of affective connotations may help better understand human-model interactions. LLMs may also serve as useful tools for researchers seeking affective meaning estimates. We test the ability of three LLMs – GPT-4o, Mistral Large, and Llama 3.1 – to estimate human affective connotation ratings of words representing social identities, behaviours, modifiers, and settings in three language cultures: English (US), French (France), and German (Germany). We find that LLM ratings of terms correlate strongly with human ratings. However, their ratings tend to be overly extreme and patterns of correlations between meaning dimensions only loosely approximate those of human ratings. Consistent with previous findings of English-language and American biases in LLMs, we find that LLMs tend to perform better on English terms, though this pattern varies somewhat by meaning dimension and the type of term in question. We explore how LLMs might contribute to scholarship on affective connotations – by acting as tools for measurement – and how scholarship on affective connotations might contribute to generative language models – by guiding exploration of model biases.
The persistently lower participation of women in entrepreneurial activities constitutes a significant economic and societal problem. This study investigates the entrepreneurial intentions (EI) of university students and graduates from the University of Applied Sciences Potsdam from a gender-specific perspective, with the central aim of identifying the reasons for the continuing differences in EIs between men and women. The theoretical framework is based on the Theory of Planned Behavior (TPB), which was extended in this study by the construct of entrepreneurial self-identity to gain a more comprehensive understanding of EI. Using structural equation modeling, an analysis was conducted for the entire cohort as well as stratified by gender, examining how attitude, social norms, perceived behavioral control, and entrepreneurial self-identity influence EI. The results of the online survey, in which 414 students and graduates participated between June 2nd and July 14th, 2023, show that men exhibit significantly higher EIs than women. Furthermore, it was demonstrated that risk-taking propensity contributes to these gender differences. Moreover, perceived behavioral control and parental role models proved to be crucial determinants for the EIs of women, while these factors did not significantly relate to the intentions of men. The analysis underscores the complexity of gender differences in EIs and implies that considering gender-specific factors in targeted support measures for universities can help reduce gender differences and thus better leverage the entrepreneurial potential of women.
This case study presents an innovative approach for explaining wildfire susceptibility through a web-based Geospatial eXplainable Artificial Intelligence (GeoXAI) system. By addressing limitations in traditional GeoXAI tools, such as the lack of geographical context for model predictions and local explanation, this system integrates state-of-the-art XAI methods with open-source geospatial technologies. Applied to the wildfire-prone regions of Berlin and Brandenburg, Germany, the system combines environmental, topographic, and meteorological features derived from high-resolution geospatial data for training a Random Forest (RF) model. The web-based GeoXAI system enables interactive exploration of the model output and its features, allowing users to visualize wildfire susceptibility, examine feature contributions, and correlate predictions with spatial patterns through post-hoc interpretability. By employing post-hoc explanation methods like SHAP, the system offers clear insights into model predictions by analyzing feature contributions after training, which helps users better understand AI-driven outcomes. Designed with a user-centered approach, the platform promotes trust and usability through transparent predictions, interactive geovisualizations, and local explanations, allowing users to navigate spatial data intuitively by exploring overviews, focusing on specific regions, and accessing detailed insights on demand. This work highlights the potential of combining GeoXAI with machine learning to improve decision-making in wildfire prevention and management.
Life cycle assessments (LCAs) in the construction sector often analyse buildings or their individual components. Applying LCA to determine the environmental impact of entire settlements is less established and the structural infrastructure is often not taken into account. The research project ‘Q-LCA - Analysis of the ecological impacts of different settlement types in new urban development projects over their life cycle’ follows the objective of determining and comparing the material flows, energy consumption including grey energy and the associated emissions of urban settlement components with a focus on global warming potential (GWP). Based on a modular approach, the GWP for 972 different settlement scenarios was determined through an LCA-based model in which six key parameters - building type, settlement density, road layout, building construction method, energy efficiency level and heating system - were systematically combined. The study demonstrates how modularity enables the assessment of large-scale systems such as urban settlements, contributing to an enhanced reflection of their inherent heterogeneity. Besides quantifying the infrastructure share of settlements’ GWP, further results indicate a high influence of operational energy consumption as well as choice of construction method on the area-based GWP. Underground garages are moreover responsible for high GWPs in densified settlements with large building types. This research fills a critical gap in existing literature by emphasising the potential of modular LCA approaches to assess urban development and additionally provides valuable insights for urban planners as well as policy makers seeking to lower environmental impact, identify circularity potentials and mitigate climate change effects in settlements.
Critical Interactivity
(2025)
We propose critical interactivity as a concept to study and design the dynamic and transitory aspects of data visualizations. Theoretically, interactivity is often described as the means to support analytical tasks, while in practice, it encompasses the techniques that alter visual representations. These notions are a useful starting point to study the role of interactivity in critical engagements with data visualizations. At the core of critical interactivity is the negotiation of authority and agency: authority as authors provide structure and context, and agency as viewers navigate and interpret the data on their own terms. This raises the critical question: who has the power to control the visualization? Drawing from four case studies in science communication, art history, anthropology, and climate advocacy, we examine how critical interactivity links exploration and narration. We reflect on the effort involved in preparing data and propose design strategies for implementing critical interactivity in data visualization.