Kristina Gligoric

All Publications

• People who share encounters with racism are silenced online by humans and machines, but a guideline-reframing intervention holds promise. Proceedings of the National Academy of Sciences of the United States of America Lee, C., Gligorić, K., Kalluri, P. R., Harrington, M., Durmus, E., Sanchez, K. L., San, N., Tse, D., Zhao, X., Hamedani, M. G., Markus, H. R., Jurafsky, D., Eberhardt, J. L. 2024; 121 (38): e2322764121

  Abstract

  Are members of marginalized communities silenced on social media when they share personal experiences of racism? Here, we investigate the role of algorithms, humans, and platform guidelines in suppressing disclosures of racial discrimination. In a field study of actual posts from a neighborhood-based social media platform, we find that when users talk about their experiences as targets of racism, their posts are disproportionately flagged for removal as toxic by five widely used moderation algorithms from major online platforms, including the most recent large language models. We show that human users disproportionately flag these disclosures for removal as well. Next, in a follow-up experiment, we demonstrate that merely witnessing such suppression negatively influences how Black Americans view the community and their place in it. Finally, to address these challenges to equity and inclusion in online spaces, we introduce a mitigation strategy: a guideline-reframing intervention that is effective at reducing silencing behavior across the political spectrum.

  View details for DOI 10.1073/pnas.2322764121

  View details for PubMedID 39250662

• Revealed versus potential spatial accessibility of healthcare and changing patterns during the COVID-19 pandemic. Communications medicine Gligorić, K., Kamath, C., Weiss, D. J., Bavadekar, S., Liu, Y., Shekel, T., Schulman, K., Gabrilovich, E. 2023; 3 (1): 157

  Abstract

  Timely access to healthcare is essential but measuring access is challenging. Prior research focused on analyzing potential travel times to healthcare under optimal mobility scenarios that do not incorporate direct observations of human mobility, potentially underestimating the barriers to receiving care for many populations.We introduce an approach for measuring accessibility by utilizing travel times to healthcare facilities from aggregated and anonymized smartphone Location History data. We measure these revealed travel times to healthcare facilities in over 100 countries and juxtapose our findings with potential (optimal) travel times estimated using Google Maps directions. We then quantify changes in revealed accessibility associated with the COVID-19 pandemic.We find that revealed travel time differs substantially from potential travel time; in all but 4 countries this difference exceeds 30 minutes, and in 49 countries it exceeds 60 minutes. Substantial variation in revealed healthcare accessibility is observed and correlates with life expectancy (⍴=-0.70) and infant mortality (⍴=0.59), with this association remaining significant after adjusting for potential accessibility and wealth. The COVID-19 pandemic altered the patterns of healthcare access, especially for populations dependent on public transportation.Our metrics based on empirical data indicate that revealed travel times exceed potential travel times in many regions. During COVID-19, inequitable accessibility was exacerbated. In conjunction with other relevant data, these findings provide a resource to help public health policymakers identify underserved populations and promote health equity by formulating policies and directing resources towards areas and populations most in need.

  View details for DOI 10.1038/s43856-023-00384-9

  View details for PubMedID 37923904

  View details for PubMedCentralID PMC10624905