On January 31st from 3:00 – 4:00 pm, CDWG will host Dr.Yiwei Xu. Yiwei Xu is a Postdoctoral Scholar at the UW Center for an Informed Public and Information School, she’s also a Data Science Postdoctoral Fellow at the UW eScience Institute. She will share her work on using digital and computational approaches to conduct public health communication research. She will share two studies; Study 1 was published in Health Communication titled “Collective Information Seeking During a Health Crisis: Predictors of Google Trends During COVID-19”; Study 2 is work in progress titled “Community Characteristics Predict Local News Agenda Building about Racial Health Disparities”. CDWG Will be Hybrid in Winter Quarter 2024. Attend in-person in 223 Raitt Hall (The Demography Lab) or on Zoom (register here).

The National Science Foundation’s Social, Behavioral and Economics Directorate encourages research proposals that expand the breadth and depth of scholarship in the science of bias, prejudice and discrimination. SBE highly encourages proposals submitted in response to its Dear Colleague Letter to plan their research in partnership with communities directly impacted by bias, prejudice, and discrimination such that the experiences and perspectives of those directly impacted by bias and discrimination are reflected in the approach. Read the full letter here. 

Join CSSS for a seminar by Hana Sevcikova, titled “Probabilistic Subnational Population Projections“. The seminar will take place on Wednesday, Jan. 31st at 12:30 in 409 Savery Hall and on Zoom (register here). Hana Sevcikova is a senior research scientist at the CSSS. She works on developing methods for probabilistic population projection, national and subnational. She has developed various demographic R packages that the United Nations Population Division has been using to produce the World Population Prospects. She also works as a data scientist on land use modeling for the Puget Sound Regional Council.

Abstract: Population projections provide predictions of future population sizes for an area. Historically, most existing population projections have been produced using deterministic or scenario-based approaches, and did not assess uncertainty about future population change. Starting in 2015, however, the United Nations has produced probabilistic population projections for all countries using a Bayesian approach. There is also considerable interest in subnational probabilistic population projections, for example at the state and county levels. These are needed by local governments for planning, by the private sector for strategic decision-making, and by researchers, particularly in the health and social science research on subnational variation and inequality. A direct application of the UN approach to the subnational context has not turned out to be fully satisfactory, because within-country correlations in fertility and mortality are generally larger than between-country ones, migration is not constrained in the same way, and there is a need to account for college and other special populations, particularly at the county level. We propose an extension to the national framework that deals with these challenges and gives accurate and well-calibrated forecasts and forecast intervals.

CSDE Trainee Elizabeth Pelletier (Evans School of Public Policy & Governance) will present her research at the Evans School seminar on Wednesday, Jan. 31st from 11:30-12:30PM in 360 Parrington Hall. Pelletier’s talk is titled “The Effects of Washington’s Paid Family and Medical Leave Policy on Maternal Employment”.

Abstract: Parents often experience unstable employment and volatile earnings around the time a child is born. Consequently, household income frequently falls at precisely the time families need increased resources to support a new child’s needs. Paid leave has emerged as a potentially promising way to smooth employment disruptions, support caregiving, and reduce inequalities by allowing more parents to afford time off. This paper studies the use and effects of a new Paid Family and Medical Leave (PFML) policy in Washington state among a key population of interest: mothers of newborns. Pelletier describes use of the policy in its first few years, examining what share of eligible mothers claimed PFML and how these take-up rates varied across demographic and employment characteristics and over time as the policy rolled out. Next, she uses a regression discontinuity design to estimate the causal effect of PFML on mothers’ employment trajectories, leveraging the policy’s discontinuous eligibility cutoff to compare outcomes among mothers whose work histories place them right above and below the cutoff. Pelletier estimates the effects of PFML on employment status, earnings and hours levels and volatility, and employer continuity among mothers around a birth. This is a practice job talk session and your attendance and valuable, constructive feedback would be greatly appreciated!