Jonathan St-Onge

h-index36
2papers

2 Papers

22.9CYApr 23
Taste for Privacy: How Context, Identity, and Lived-Experience Shape Information Sharing Preferences

Juniper Lovato, Laurent Hébert-Dufresne, Mohsen Ghasemizade et al.

Privacy preferences are not fixed individual traits, they depend on context and lived experiences. In this study, we analyze 2,912 survey responses from 782 college students collected over seven survey periods during 2023 and 2024. We ask about their usage of social media, the security settings of their accounts, and measure their comfort in sharing personally identifiable information (PII) across 17 different institutional contexts. Compared to past research, we observe a large shift towards private accounts, going from 1/3rd private in 2007 to 2/3rds in 2024, and find that participants' discomfort sharing PII with social media platforms strongly predicts their privacy settings. Beyond social media, we identify a stable ranking of institutional trust, though some institutions, like the police, show high variability reflecting divergent lived experiences. Traditionally marginalized groups and participants having faced adverse childhood experiences show more discomfort with institutions of power, especially in areas where they face greater vulnerability. We argue for context-adaptive privacy settings that recognize institutional relationships and demographic vulnerabilities, moving beyond one-size-fits-all consent frameworks toward contextually appropriate data governance.

CLJun 26, 2025
A suite of allotaxonometric tools for the comparison of complex systems using rank-turbulence divergence

Jonathan St-Onge, Ashley M. A. Fehr, Carter Ward et al.

Describing and comparing complex systems requires principled, theoretically grounded tools. Built around the phenomenon of type turbulence, allotaxonographs provide map-and-list visual comparisons of pairs of heavy-tailed distributions. Allotaxonographs are designed to accommodate a wide range of instruments including rank- and probability-turbulence divergences, Jenson-Shannon divergence, and generalized entropy divergences. Here, we describe a suite of programmatic tools for rendering allotaxonographs for rank-turbulence divergence in Matlab, Javascript, and Python, all of which have different use cases.