A workflow for human-centered machine-assisted hypothesis generation: Commentary on Banker et al. (2024).

Large language models (LLMs) have the potential to revolutionize a key aspect of the scientific process-hypothesis generation. Banker et al. (2024) investigate how GPT-3 and GPT-4 can be used to generate novel hypotheses useful for social psychologists. Although timely, we argue that their approach overlooks the limitations of both humans and LLMs and does not incorporate crucial information on the inquiring researcher's inner world (e.g., values, goals) and outer world (e.g., existing literature) into the hypothesis generation process. Instead, we propose a human-centered workflow (Hope et al., 2023) that recognizes the limitations and capabilities of both the researchers and LLMs. Our workflow features a process of iterative engagement between researchers and GPT-4 that augments-rather than displaces-each researcher's unique role in the hypothesis generation process. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Mental health concerns precede quits: shifts in the work discourse during the Covid-19 pandemic and great resignation.

To study the causes of the 2021 Great Resignation, we use text analysis and investigate the changes in work- and quit-related posts between 2018 and 2021 on Reddit. We find that the Reddit discourse evolution resembles the dynamics of the U.S. quit and layoff rates. Furthermore, when the COVID-19 pandemic started, conversations related to working from home, switching jobs, work-related distress, and mental health increased, while discussions on commuting or moving for a job decreased. We distinguish between general work-related and specific quit-related discourse changes using a difference-in-differences method. Our main finding is that mental health and work-related distress topics disproportionally increased among quit-related posts since the onset of the pandemic, likely contributing to the quits of the Great Resignation. Along with better labor market conditions, some relief came beginning-to-mid-2021 when these concerns decreased. Our study underscores the importance of having access to data from online forums, such as Reddit, to study emerging economic phenomena in real time, providing a valuable supplement to traditional labor market surveys and administrative data. Supplementary Information: The online version contains supplementary material available at 10.1140/epjds/s13688-023-00417-2.

Opening the doors for spillovers: a contingency view of the effects of work from home on the work-home interface.

Why do employees experience work from home (WFH) differently? We draw on boundary theory to explain how WFH influences employees' work-home interface. WFH intensity increases negative spillovers (i.e., work-to-home conflict and home-to-work conflict) and positive spillovers (i.e., work-to-home enrichment and home-to-work enrichment) between the work and home domains. Negative spillovers can be mitigated through high-quality work equipment and beneficial spatial conditions at home. Domain centrality predicts who can benefit from increased WFH intensity. We test our theory with a sample of 545 employees, obtained through a two-step random sampling procedure in the city of Munich/Germany during the COVID-19 pandemic. We find that WFH intensity increases work-to-home conflict and home-to-work enrichment, affecting employees' relationship satisfaction and job satisfaction. High-quality work equipment mitigates the detrimental effects of WFH. Employees with a high family centrality can reap benefits of more WFH because they experience more home-to-work enrichment. The simultaneous desirable and detrimental effects of WFH intensity can partly explain why studies have found heterogenous WFH experiences among employees.