CSDE Computational Demography Working Group (CDWG): Jing Xu & Yehong Deng (05/13/26)
The Computational Demography Working Group welcomes Dr. Jing Xu and Yehong Deng from University of Washington, who will present on
Youth & Truth in Northern Ireland: LLM-Empowered Knowledge Graph Analysis of History Textbooks.” The talk is hybrid and will take place on May 13th in Raitt 223 from 10-11 AM (Pacific). Use this link to register and log onto Zoom. To receive the newsletter from CDWG, participants may choose to join our listserv here. Click read more to see the talk abstract and speaker bios.
Youth & Truth in Northern Ireland: LLM-Empowered Knowledge Graph Analysis of History Textbooks.” The talk is hybrid and will take place on May 13th in Raitt 223 from 10-11 AM (Pacific). Use this link to register and log onto Zoom. To receive the newsletter from CDWG, participants may choose to join our listserv here. Click read more to see the talk abstract and speaker bios.
Title: Youth & Truth in Northern Ireland: LLM-Empowered Knowledge Graph Analysis of History Textbooks
Abstract: Post-conflict societies face a persistent challenge: how to reconcile divergent historical memories embedded in educational materials and teach the next generation. Northern Ireland provides a significant test case to examine this question, where the school system remains largely divided along group identity lines in a polarized society. Our larger project on youth and truth in NI, sponsored by the Templeton World Charity Foundation, found that history curriculum in Catholic Schools and state (Protestant) schools focus on different time periods, Option 1 (1921-1949) and Option 2 (Troubles era), during a crucial phase in students’ formative years (KS4, 14-16-year-old).
This talk presents a novel computational analysis of history textbooks focused on the two periods, Option1 and Option 2, combining LLM-powered knowledge graph (KG) with narrative network analysis. Drawing on a refined ontology, we extract subject–predicate–object triples from a corpus of history textbooks, yielding knowledge graphs of approximately 500–800 nodes and 600–1,000 edges per tradition. We analyze structural properties including centrality, reachability, community clustering, and sentiment.
Our comparative analysis reveals systematic divergences in how historical events, entities and figures are positioned across the two traditions. Option 1 textbooks center on entities and events associated with WWII and Anglo-Irish constitutional relations, while Option 2 texts focus on civil rights, internment, and power-sharing arrangements in the Troubles era. Sentiment analysis further shows that the same entities receive markedly different evaluative framings across corpora. These structural asymmetries in narrative construction may reflect and reinforce the polarized historical identities that post-conflict education efforts seek to bridge.
Learn more about Dr. Jing Xu: Affiliate Professor in Anthropology & Co-Director of the Center for Globally Beneficial AI at the University of Washington. Xu’s research integrates ethnographic, experimental and computational methods to study moral development, social learning, and AI ethics in cultural contexts. She studied at Tsinghua University (Beijing) before moving to the U.S., got her PhD in anthropology from Washington University in St. Louis, and completed postdoctoral work in psychology at the University of Washington. She is the author of two monographs, “The Good Child” (2017) and “‘Unruly’ Children” (2024). She is an Associate Editor of American Anthropologist.
Yehong Deng is a fourth-year PhD student in Sociology at the University of Washington. Her research sits at the intersection of computational social science, digital humanities, and peace education, with a focus on how historical narratives are structured and transmitted in post-conflict contexts. Her dissertation applies large language models and network analysis to study how Northern Ireland history textbooks across denominational traditions construct divergent historical narratives, drawing on knowledge graph extraction and comparative discourse analysis.
Postdoctoral Researcher, National Study of Older Never-Married Adults (NSONMA) – Vanderbilt University (05/18/26)
CACHE Seminar: Tracking the Mortality Burden Associated with Extreme Weather Events in the United States (05/15/26)
Join CACHE on May 12 at 11 AM PT for a online seminar on, “Tracking the Mortality Burden Associated with Extreme Weather Events in the United States: Implications for Older Adult Health,” featuring Dr. Kai Chen of Yale School of Public Health. Extreme climate-related hazards, such as wildfire smoke, extreme temperatures (both heat and cold), floods, and drought, are increasingly recognized as major threats to human health and well-being in the United States. These events contribute to substantial premature mortality, which in turn imposes significant economic losses on society. However, the public often lacks clear, science-based information that captures the scale of these damages and makes them accessible across different regions. To address this gap, the Climate, Health, and Environment Nexus (CHEN) Lab at the Yale Center on Climate Change and Health recently developed a dashboard that attributes premature mortality in the contiguous United States to these extreme climate events: XToll: eXtreme-weather Toll Tracker. Register here.
Dr. Kai Chen will introduce the XToll dashboard and its underlying research on the national county-level mortality burden of heat, cold, wildfire smoke, floods, and drought. He will also highlight the health effects of non-optimal temperatures and wildfire smoke on older adults’ cardiovascular health, emphasizing the heightened vulnerability of aging populations to these environmental stressors. Extreme climate-related hazards, such as wildfire smoke, extreme temperatures (both heat and cold), floods, and drought, are increasingly recognized as major threats to human health and well-being in the United States. These events contribute to substantial premature mortality, which in turn imposes significant economic losses on society. More information can be found here.
Request for Proposals: Advancing Well-Being in the Arts and Economic Mobility (LOIs due 05/12/26)
As a part of its Advancing Well-Being in the Arts Initiative’s Field Studies program, Wallace is interested in funding a small set of research studies that investigate aspects of how community-based arts organizations contribute to the economic mobility of their communities. “Communities” may include organizational staff, artists, audiences, program participants, local constituents served, and/or others as defined in proposals. For this RFP, the Wallace Foundation broadly defines and understands economic mobility, and pathways to economic mobility, as emerging through access to training and preparation, expanded social and professional networks, high quality jobs, as well as to basic needs such as safe neighborhoods, housing, health care, and food. However, we are eager to learn, through the studies to be funded, how arts organizations themselves conceptualize, define, and support economic mobility in their communities. To be invited to submit a full proposal, you must submit a 3-4 page letter of interest by May 12. Learn more here.
*New* Call for Paper Proposals: Special Issue of the Journal of Health Policies, Politics and Law on “Community Organizing, Power, and Politics” (05/15/26)
The Journal of Health Politics, Policy and Law (JHPPL) invites proposal submissions by May 15 for a special issue on “Community Organizing, Power, and Politics.” JHPPL invites submissions interrogating how community organizers have advanced change across broad topical areas encompassing health services and the structural determinants of health (e.g., tenant protections, medical debt relief, paid leave, Medicaid benefits). JHPPL is also interested in work that operationalizes power as a structural determinant of health (e.g., voting rights or restrictions, collective bargaining, incarceration rates) and examines health outcomes. JHPPL seeks research that takes a broad view on organizing and power, addressing any or all of the multiple dimensions of power, and work that addresses both how power might be built or how it might be broken (Michener 2022) to advance community and population health.
All methodological approaches and from multiple disciplinary orientations are welcomed, including political science, health policy, public health, communication, sociology, anthropology, and law, and JHPPL particularly invite contributions from community members, community organizers, and community-engaged researchers. Submit paper proposals by May 15 via email to Jed Cohen, JHPPL’s managing editor, at jhppleditor@dukeupress.edu. Please put “Community Organizing, Power, and Politics” in the subject line.
Submission instructions
JHPPL is interested in proposals for submissions within two categories:
- Commentaries (with or without empirical data, can include personal accounts and narratives) (full manuscripts will be <4000 words)
- Full empirical research articles (any methodology) (full manuscripts will be <9000 words)
The special issue process will proceed in two stages. Proposals describing the manuscript should be submitted by May 15, 2026. Proposals for empirical research articles should be submitted as a structured abstract with the following sections: Authors and Affiliations, Research Objective(s), Motivation/Theory, Research Design, Preliminary Results, and Implications. Proposals for commentaries do not need to be structured. All proposals, whether for research articles or commentaries, have a limit of 500 words.
The special issue co-editors will review all submissions and extend invitations for full papers by June 1st. Invited submissions will be due by September 1, 2026.
Submit paper proposals via email to Jed Cohen, JHPPL’s managing editor, at jhppleditor@dukeupress.edu. Please put “Community Organizing, Power, and Politics” in the subject line.
Associate Director of HPRC, Demography – Kinder Institute for Urban Research, Rice University (Ongoing)
Senior Mixed-Methods Researcher, Employment and Economic Opportunity – AIR (Ongoing)
CSDE Computational Demography Working Group: Yehong Deng and Jing Xu (05/13/26)
The Computational Demography Working Group welcomes Dr. Jing Xu and Yehong Deng from University of Washington, who will present on
Youth & Truth in Northern Ireland: LLM-Empowered Knowledge Graph Analysis of History Textbooks.” The talk is hybrid and will take place on May 13th in Raitt 223 from 10-11 AM (Pacific). Use this link to register and log onto Zoom. To receive the newsletter from CDWG, participants may choose to join our listserv here. Click read more to see the talk abstract and speaker bios.
Youth & Truth in Northern Ireland: LLM-Empowered Knowledge Graph Analysis of History Textbooks.” The talk is hybrid and will take place on May 13th in Raitt 223 from 10-11 AM (Pacific). Use this link to register and log onto Zoom. To receive the newsletter from CDWG, participants may choose to join our listserv here. Click read more to see the talk abstract and speaker bios.
Title: Youth & Truth in Northern Ireland: LLM-Empowered Knowledge Graph Analysis of History Textbooks
Abstract: Post-conflict societies face a persistent challenge: how to reconcile divergent historical memories embedded in educational materials and teach the next generation. Northern Ireland provides a significant test case to examine this question, where the school system remains largely divided along group identity lines in a polarized society. Our larger project on youth and truth in NI, sponsored by the Templeton World Charity Foundation, found that history curriculum in Catholic Schools and state (Protestant) schools focus on different time periods, Option 1 (1921-1949) and Option 2 (Troubles era), during a crucial phase in students’ formative years (KS4, 14-16-year-old).
This talk presents a novel computational analysis of history textbooks focused on the two periods, Option1 and Option 2, combining LLM-powered knowledge graph (KG) with narrative network analysis. Drawing on a refined ontology, we extract subject–predicate–object triples from a corpus of history textbooks, yielding knowledge graphs of approximately 500–800 nodes and 600–1,000 edges per tradition. We analyze structural properties including centrality, reachability, community clustering, and sentiment.
Our comparative analysis reveals systematic divergences in how historical events, entities and figures are positioned across the two traditions. Option 1 textbooks center on entities and events associated with WWII and Anglo-Irish constitutional relations, while Option 2 texts focus on civil rights, internment, and power-sharing arrangements in the Troubles era. Sentiment analysis further shows that the same entities receive markedly different evaluative framings across corpora. These structural asymmetries in narrative construction may reflect and reinforce the polarized historical identities that post-conflict education efforts seek to bridge.
Learn more about Dr. Jing Xu: Affiliate Professor in Anthropology & Co-Director of the Center for Globally Beneficial AI at the University of Washington. Xu’s research integrates ethnographic, experimental and computational methods to study moral development, social learning, and AI ethics in cultural contexts. She studied at Tsinghua University (Beijing) before moving to the U.S., got her PhD in anthropology from Washington University in St. Louis, and completed postdoctoral work in psychology at the University of Washington. She is the author of two monographs, “The Good Child” (2017) and “‘Unruly’ Children” (2024). She is an Associate Editor of American Anthropologist.
Yehong Deng is a fourth-year PhD student in Sociology at the University of Washington. Her research sits at the intersection of computational social science, digital humanities, and peace education, with a focus on how historical narratives are structured and transmitted in post-conflict contexts. Her dissertation applies large language models and network analysis to study how Northern Ireland history textbooks across denominational traditions construct divergent historical narratives, drawing on knowledge graph extraction and comparative discourse analysis.