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1. Disasters and corruption: public expectations and tolerance—evidence from Mexico

   https://doi.org/10.1111/disa.12585  

   Gawronski, Vincent T.; Levitt, Barry S.; Olson, Richard S. (July 2023, Disasters)

   Disaster corruption is a vexing problem, damaging state legitimacy and exacerbating human suffering. Mexico has a history of both major disasters and persistently high levels of corruption. A magnitude 7.1 earthquake in 2017 provided an opportunity to study change over time in expectations and tolerance of corruption in disaster relief. Twenty years earlier, Mexico City residents expected, on average, essentially three out of 10 hypothetical trucks loaded with humanitarian assistance to be lost to corruption but expressed near zero tolerance of such conduct. By 2018–19, Mexico City residents expected more than one‐half of all relief, six out of 10 trucks, to be stolen, and could tolerate three out of 10 trucks being pilfered. Similar results were found at the national level. Hence, Mexicans appear to be giving up on the state. Addressing corruption in disaster risk reduction and humanitarian relief specifically might provide a template for improving public trust across other state institutions. 

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2. Reconceptualizing urban flood modeling: Toward intersectional and equitable urban flood risk planning

   https://doi.org/10.1016/j.scs.2025.106578  

   Scolio, Madeline; Amur, Achira; Olson, Emma; Smith, Virginia; Wadzuk, Bridget; Homet, Kate; Devlin, Eric; Kremer, Peleg (July 2025, Sustainable Cities and Society)

   Urban flooding, fueled by climate change and rapid urbanization, presents significant challenges for cities around the world. In the United States, this is of particular concern as we see older cities reaching their maximum development density, and newer cities developing to the edge of their boundaries. The dynamic nature of cities and the people that live in them complicate urban flood risk modeling. This paper highlights the need to reconceptualize urban flooding from a spatially and temporally intersectional perspective by analyzing the patterns of socio-economic and bio-physical data across eight US cities to illustrate how spatial flood risk is driven by place-specific factors. Here, we demonstrate the need for a holistic understanding of flood risk, which acknowledges both the deep histories and uncertain futures specific to each city to promote urban flood resilience and environmental justice. Legacies of racialized development continue to influence the spatial heterogeneity of urban flood risk. Thus, centering the ways past injustice has shaped the environment is critical to highlighting inequities in who and where is at increased risk of flooding. The varying impacts of climate change on flooding in different cities, as well as the actions city governments have taken in response to flood events, inform risk and should be included in modeling efforts. There are many challenges in incorporating new temporal dynamics into flood risk modeling, such as data availability, creating a necessity for a greater understanding of flood impact. This is required not only to fully comprehend the impacts of flooding but also to identify appropriate, necessary, and community-sensitive flood interventions as well as to optimize the impact of adaptive measures. Considering historical and future drivers of risk, intersectional flood risk models are required to promote more equitable and effective resilience efforts. This approach will allow urban flood planners and engineers to gain a deeper understanding of how to promote climate resilience while overcoming the reinforcement of discriminatory development and management patterns. 

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3. Climate change and municipal finance: Ordinary innovations for just urban transitions

   https://doi.org/10.1177/00420980241286362  

   Diezmartínez, Claudia_V; Short_Gianotti, Anne_G (November 2024, Urban Studies)

   As cities worldwide increasingly adopt commitments towards climate justice, questions remain about the ways that city governments will be able to fund more just climate efforts. While the use of novel debt financing schemes has been examined in the literature for its justice implications, scholars have rarely interrogated how the more mundane tools and practices of municipal finance can be applied to enable more just urban transitions. Here, we use the USA as a case study to analyse the impacts of climate change and climate action on municipal budgets and to examine how cities are adapting their financial tools and practices to advance climate action and climate justice efforts. We employ a mixed-methods research design that combines 34 expert interviews with a systematic content analysis of municipal budgets from 15 US cities of different sizes. We find that both climate change and climate action can contribute to cities’ fiscal vulnerability by imposing additional expenditures and/or reducing municipal revenues. While most cities lack transparency about their investments in climate action and climate justice, some city governments are implementingordinary innovationsthat embed climate and justice criteria into budgetary practices and funding tools. These ordinary innovations reveal that cities are beginning to reimagine municipal finance in the service of more just climate futures. 

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4. Developing a social sensing index for monitoring place-oriented mental health issues using social media (twitter) data

   https://doi.org/10.1007/s44212-023-00033-5  

   Park, Jaehee; Tsou, Ming-Hsiang; Nara, Atsushi; Cassels, Susan; Dodge, Somayeh (December 2024, Urban Informatics)

   Abstract Research shows that certain external factors can affect the mental health of many people in a community. Moreover, the importance of mental health has significantly increased in recent years due to the COVID-19 pandemic. Many people communicate and express their emotions through social media platforms, which provide researchers with opportunities to examine insights into their opinions and mental state. While social sensing studies using social media data have flourished in the last decade, many studies using social media data to detect and predict mental health status have focused on the individual level. In this study, we aim to generate a social sensing index for mental health to monitor emotional well-being, which is closely related to mental health, and to identify daily trends in negative emotions at the city level. We conduct sentiment analysis on Twitter data and compute entropy of the degree of sentiment change to develop the index. We observe sentiment trends fluctuate significantly in response to unusual events. It is found that the social sensing index for mental health reflects both city-wide and local events that trigger negative emotions, as well as areas where negative emotions persist. The study contributes to the growing body of research that uses social media data to examine mental health at a city-level. We focus on mental health at the city-level rather than individual, which provides a broader perspective on the mental health of a population. Social sensing index for mental health allows public health professionals to monitor and identify persistent negative sentiments and potential areas where mental health issues may emerge. 

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5. Social predictors of doctoral student mental health and well-being

   https://doi.org/10.1371/journal.pone.0274273  

   Zhang, Feng; Litson, Kaylee; Feldon, David F. (September 2022, PLOS ONE)

   Miettunen, Jouko (Ed.)

   Graduate students’ mental health and well-being is a prominent concern across various disciplines. However, early predictors of mental health and well-being in graduate education, specifically doctoral education, have rarely been studied. The present study evaluated both the underlying latent classification of individuals’ mental well-being and predictors of those classifications. Results estimated two latent classes of students’ mental health and well-being: one class with generally high levels of mental well-being and one with lower levels of mental well-being. Regression analyses showed that mentoring in the second year of doctoral study, certainty of choice in the third year, and both academic development and sense of belonging in the fourth year were positive predictors of membership in the higher mental well-being class. In contrast to some prior studies, demographic variables were not related to the identified well-being classifications. Regression analyses further showed that mental well-being was negatively related to participants’ number of publications and research self-efficacy, indicating a problematic relationship between scholarly productivity and confidence and well-being. These findings may be used to identify and provide targeted support for students who are at-risk for having or developing lower levels of mental well-being in their graduate programs. 

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