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Explores gender and class dynamics in housing appropriation, emphasizing the importance of listening to women's perspectives and rethinking spatial solutions to social issues.
Explores the analysis of mood expressed on Twitter using longitudinal data and text analysis tools, emphasizing the importance of considering biased data.
Explores the importance of causality for robust machine learning, covering ideal datasets, missing data problems, graphical models, and interference models.
Explores the integration of an intersectional gender perspective in implementation research, emphasizing participatory approaches and challenges in knowledge translation.
