Nomadic Academic Experiment: Part 1
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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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About me
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I have a new preprint out on SocArXiv: An Empirical Investigation into the Utility of Large Language Models in Open-Ended Survey Data Categorization.
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On October 29th, 2025, I had the privilege of presenting at the University of Washington on how large language models can augment social science research. The presentation focused on CatLLM, an open-source Python package I developed to address a common challenge in demographic and social science research: analyzing open-ended survey responses and complex data at scale.
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On July 1st, 2025, I had the opportunity to present joint research with Dr. William H. Dow, Professor of Health Policy and Management and Director of the Center on the Economics and Demography of Aging at UC Berkeley. Our presentation explored a fascinating contradiction in Hispanic aging: the Hispanic health paradox in cognitive outcomes.
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I presented shared work with Professor William Dow and Henry Dow, comparing sociodemographic characteristics of older Hispanic adults in U.S. immigrant populations with those in their countries of origin, using census microdata and the American Community Survey (publication pending).
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I had the opportunity to present our research on public school background and probability of enrollment in a graduate degree at the 2025 PSA conference.
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I recently presented my research at the Science Envoy “Ask a Science Envoy” event at HopMonk Tavern in Novato—my first time presenting at a brewery and to a non-academic audience. The experience taught me the importance of navigating sensitive topics like partisanship and belief in science, especially when audience members began debating the subject.
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I’m super grateful to the Dominican team of The Caribbean American Dementia and Aging Study (CADAS).
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In our upcoming paper, “Measuring and Modeling the Impact of Partisan Differences in Health Behaviors on COVID-19 Dynamics,” we use a three-group Susceptible-Infected-Recovered model to highlight the importance of incorporating partisan differences into models of disease transmission. In this blog post, I want to fully explain what is happening in the background for readers who may be interested in utlizing it themselves. For those users, we also built an R shiny app (soon to be published as well). The link to the shiny app will be: here.
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I’m super grateful to the Puerto Rican team of The Caribbean American Dementia and Aging Study (CADAS). We got a lot done and things are moving quickly! Looking forward to visiting again soon.
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I had the opportunity to present our research on public school background and probability of enrollment in a graduate degree at the 2024 CAIR conference.
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The impact of non-pharmaceutical interventions and protective health behaviors, such as the use of face masks and physical distancing, on COVID-19 dynamics is well-documented, but sub-group heterogeneities in the adoption of these behaviors remains understudied. In this paper, we describe partisan differences in the adoption of protective health behaviors, and model how these differences can impact the dynamics of COVID-19.
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I have been selected as a Science Envoy for Wonderfest: The Bay Area Beacon of Science.
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In the world of data analysis, ensuring the accuracy and consistency of datasets is crucial, especially when dealing with entities like school names that may be spelled differently across various sources. This discrepancy can pose significant challenges when trying to match records from different datasets. Traditional methods of data cleaning may fall short in addressing these inconsistencies effectively.
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This first ever blog post is in honor of my recently passed little man, Charlie the cat, who for 12 years went together with me through thick and thin. He was the best cat anyone could’ve asked for, and no other will ever be able to replace him. I will miss you dearly, Charles, aka “Chester.” I love you always.
Short description of portfolio item number 1
Short description of portfolio item number 2 
Published in The International Journal of Aging and Human Development, 2022
This paper is was written while I was an undergraduate and published during my first year of graduate school.
Recommended citation: Soria C, Lawton L. Connecting Fathers: Fathers’ Impact on Adult Children’s Social Networks. The International Journal of Aging and Human Development. 2023;96(1):19-32. doi:10.1177/00914150221106645 hhttps://journals.sagepub.com/doi/full/10.1177/00914150221106645
Published in Frontiers in Public Health, 2022
This commentary examines the disparities in COVID-19 mortality rates between the U.S. and India, exploring demographic dynamics and contextual factors contributing to the “Indian death paradox.”
Recommended citation: Zanwar PP, Wallace KL, Soria C, Perianayagam A. Commentary: Examining contextual factors contributing to differentials in COVID-19 mortality in U.S. vs. India. Front Public Health. 2022;10:995751. doi:10.3389/fpubh.2022.995751 https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2022.995751/full
Published in American Journal of Epidemiology, 2025
Cross-national comparisons of dementia prevalence are essential for identifying unique determinants and cultural-specific risk factors, but methodological differences in dementia classification across countries hinder global comparisons. This study maps the 10/66 algorithm for dementia classification, widely used and validated in low- and middle-income countries (LMICs), to the U.S. Aging, Demographics, and Memory Study (ADAMS), the dementia sub-study of the Health and Retirement Study, and assesses its performance in ADAMS.
Recommended citation: Jorge J Llibre Guerra, Jordan Weiss, Jing Li, Chris Soria, Ana Rodriguez-Salgado, Juan de Jesús Llibre Rodriguez, Ivonne Z Jiménez Velázquez, Daisy Acosta, Mao-Mei Liu, William H Dow, Assessing the 10/66 Dementia Classification Algorithm for International Comparative Analyses with the U.S., American Journal of Epidemiology, 2024;, kwae470, https://doi.org/10.1093/aje/kwae470 https://pubmed.ncbi.nlm.nih.gov/39745806/
Published in BMC Geriatrics, 2025
CADAS is a multi-purpose household study of aging focused on the life course determinants and consequences of health and dementia in Puerto Rico, Dominican Republic, and Cuba.
Recommended citation: Liu MM, Llibre-Guerra J, Soria C, Li J, Zayas Llerena T, Rodriguez G, Acosta D, Jiménez Velázquez I, Llibre-Rodriguez JJ, Dow WH. The Caribbean American Dementia and Aging Study: protocol for a population-based study of older adult health and dementia in Cuba, the Dominican Republic, and Puerto Rico. BMC Geriatr. 2025;25(1). doi:10.1186/s12877-025-06131-0 https://bmcgeriatr.biomedcentral.com/articles/10.1186/s12877-025-06131-0
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Despite rapidly expanding interest in fathers, scholars know little about the impact of fathers on adult health and well-being. How does the positive presence – or lack thereof - of fathers in adult children’s lives affect their social networks? Drawing on attachment theory and social capital theory to examine novel UC Berkeley Social Networks Study (UC Nets) data, I seek to extend understanding of how father attachment and socialization can influence adult social well-being. I find that individuals who name a father in their social network have significantly more social ties. Those with a “close” father have larger social networks than those who name a father who is not “close.” This has consequences for individuals’ broader networks: respondents with a “close” father report more males – but not females – in social activities networks. In contrast, having a “close” mother was associated with more females to confide in, but not males.
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Democrats tended to have lower contacts, increased mask-usage, and a higher probability of vaccination during the COVID-19 pandemic. But, what happens when Democrats live in counties where they are the minority? How does this impact their behavior?
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Joint presentation with Dr. Audrey Dorélien examining partisan differences in the adoption of protective health behaviors during COVID-19 and modeling how these differences impact disease dynamics. Using detailed survey data on partisanship, contact rates, mask usage, and vaccination rates, we demonstrated that partisan differences in health behaviors exceed racial and gender differences. We incorporated these observations into a Susceptible-Infected-Recovered (SIR) model framework that explicitly incorporates partisanship to identify the most significant mechanisms driving disease spread, emphasizing the importance of considering partisan identification in public health policy and pandemic preparedness.
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Radio interview as a Wonderfest Science Envoy on KPOO’s “Let Me Touch Your Mind” show, hosted by Marilynn Fowler. Discussed research on partisan-influenced health outcomes and how political partisanship shapes public health behaviors and disease spread.
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Presented as a Wonderfest “Science Envoy” at a public science event co-hosted with Marin Science Seminar. The talk explored how political partisanship significantly influences how different groups respond to public health guidance, affecting their adherence to protective measures against infectious diseases. Understanding partisan-based disparities in acceptance of scientific evidence helps us to predict the population-wide spread of diseases and to improve public health outcomes.
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Participated in a panel discussion on the benefits and challenges of AI in demography at the 2025 PAA Annual Meeting. Discussed use-cases and benefits/limitations of large language models (LLMs) for survey research alongside other panelists.
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Presented research with William H. Dow and Henry Dow comparing sociodemographic characteristics of Caribbean Hispanic older adult immigrants in the United States with those in their origin countries. Session chaired by Marc A. Garcia.
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Joint presentation with Dr. William H. Dow examining the Hispanic health paradox in cognitive aging. The talk explored the contradiction in Hispanic aging where Mexican migrants, despite being more socioeconomically disadvantaged, demonstrate better cognitive aging outcomes than other Hispanic migrant groups. This research contributes to understanding health disparities and the complex relationship between socioeconomic status and health outcomes in aging populations.
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Presented on computational tools that augment social science research using large language models. Introduced CatLLM—an open-source Python package that enables researchers to apply language and vision models to survey coding, image analysis, and data categorization without machine learning expertise. The talk covered practical applications in demographic research, including automated coding of open-ended survey responses and analysis of cognitive health data.
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.