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Center for Studies in Demography and Ecology

Aging with Limited Kin: Childlessness and Care Arrangements in Singapore and Thailand – Bussarawan “Puk” Teerawichitchainan

We look forward to welcoming Dr. Bussarawan “Puk” Teerawichitchainan from the National University of Singapore on Friday, April 10th, in Parrington Hall 360 and on Zoom. This seminar is co-sponsored by the Population Health Initiative. To Join By Zoom: Register HERE. Follow this link to sign up for a 1:1 meeting with Dr. Teerawichitchainan during their visit on April 10th

Rapid demographic transitions and changing family structures are increasing the number of adults aging with limited close kin. Drawing on mixed-methods evidence from Thailand and Singapore, this talk examines how childlessness and other forms of constrained kin availability shape long-term care and advance care planning in later life. Findings reveal substantial heterogeneity among childless older adults, pronounced gender differences in care vulnerabilities and planning behaviors, and persistent tensions between familistic norms and the lived realities of kin limitation. Moving beyond deficit-based framings, the presentation highlights adaptive strategies through which older adults reconfigure care and planning, and argues for reimagining kin, care, and policy in low-fertility, family-oriented societies.

Bussarawan “Puk” Teerawichitchainan is an Associate Professor of Sociology and, until December 2025, Co-Director of the Centre for Family and Population Research at the National University of Singapore. Her research examines aging, family, and the life course in Southeast Asia, with recent projects on the long-term impacts of war trauma among older Vietnamese survivors and the dynamics of childless aging in Singapore and Thailand. She is currently a Fellow at the Center for Advanced Study in the Behavioral Sciences at Stanford University.

NIH Fellowship Opportunities for Early Career Scientists (04/08/26)

Have you explored NIH Fellowship opportunities? We wanted to remind you that NIH fellowships are open to early career scientists, including at the predoctoral and postdoctoral level. NIH fellowships and are designed to provide mentored research training to enable skills’ development and experiences needed to transition into careers in the biomedical research workforce.

Through these programs, the NIH fosters innovation, collaboration, and the advancement of knowledge aimed at improving human health.

The next due date for Fellowship applications (F series) is April 8. We encourage applicants to visit the standard due dates page to stay on top of approaching deadlines.

Some helpful reminders for applicants and their supporters:

Request for Pilot Grant Proposals on Rural Population Health and Aging (INRPHA) (04/10/26)

Request for Proposals – Interdisciplinary Network on Rural Population Health and Aging With funding from the National Institute on Aging, the Interdisciplinary Network on Rural Population Health and Aging (INRPHA) invites investigators to submit proposals for pilot research that enhances understanding of the multilevel and multidimensional drivers of rural health and aging trends and disparities. Investigators may request up to $35,000. Proposals are due by Friday, April 10.

CSDE Computational Demography Working Group: Kentaro Hoffman on Inference on Predicted Data and its Implications for Demography (04/01/26)

The first Computational Demography Working Group speaker of the spring quarter will be Dr. Kentaro Hoffman, and titled, “Drawing Rhinoceroses with Algorithms: Inference on Predicted Data and Its implications for Demography”. The talk is hybrid and will take place on April 1  in Raitt 223  from 10 – 11 AM PST. Use this link to register and log onto Zoom. To receive the newsletter from CDWG, participants may choose to join our listserv here.
Title: “Drawing Rhinoceroses with Algorithms: Inference on Predicted Data and Its implications for Demography”

Abstract: Machine learning is increasingly used in demography to predict quantities that were once directly observed. Yet predictions are often treated as data, a practice that can lead to biased estimates and misleading uncertainty. This talk introduces Inference on Predicted Data (IPD), a framework for conducting valid statistical inference when outcomes are generated by black-box prediction models rather than measured directly.

I illustrate IPD through an application to verbal autopsies, where causes of death are inferred from free-text narratives using modern NLP methods, including large language models. While these models can achieve high predictive accuracy, naïvely using predicted causes of death in downstream analyses produces distorted demographic patterns. IPD-based corrections leverage a small amount of labeled data to recover valid estimates and uncertainty, even under prediction error and distribution shift.

The results highlight a key lesson for computational demography: accurate predictions alone are not enough for reliable population inference.

Learn more about Dr. Hoffman: Kentaro Hoffman is a statistician whose research focuses on inference with AI-generated and predicted data, uncertainty quantification, and responsible machine learning. He was previously a postdoctoral scholar at the University of Washington and Johns Hopkins University, working with Tyler McCormick, Peter Searson, and Scott Zeger. His work lies at the intersection of statistics, machine learning, and computational demography, with applications including verbal autopsies, global mortality estimation, electronic medical records, and active learning.

NIH Reorganizes Study Sections

NIH has been undergoing a review of its existing study section since 2019. All social and behavioral study sections were reviewed last year and has resulted in the retirement of Social Science and Population Studies (A & B) and several others.  A new Population Dynamics and Health (PDH) study section and a Social Determinants of Behavioral, Cognitive, and Psychological Health study section have been formed from the former SSPS-A and SSPS-B. They will begin reviewing applications Oct 2026. Many other new study sections may be relevant to your work. To help identify appropriate study sections, please see the Assisted Referral Tool (ART).