The impact of discrimination on trust in government institutions: A LASSO regression analysis in the Canadian context during COVID-19

Authors: Nihed Fezai *, Moktar Lamari

Affiliations:

École Nationale d'Administration Publique (ENAP), Université du Québec, Québec, Canada

Abstract

This study examines the effect of discrimination on public trust in government and public servants during the COVID-19 pandemic. Using Canadian survey data collected in 2020 (N = 36,674), we apply both logistic regression and ordinary least squares (OLS) regression to analyze how discrimination related to COVID-19 influenced trust in four public institutions. Prior to running these models, we used the Least Absolute Shrinkage and Selection Operator (LASSO) method for variable selection. The findings indicate that personal experiences of discrimination significantly reduce institutional trust, particularly when discrimination occurs online, in the workplace, or during interactions with the police. However, the results also show that a strong sense of belonging—whether to Canada, a specific province or territory, or a shared community (such as speakers of the same language)—is associated with higher levels of trust in institutions. These insights provide valuable guidance for policymakers and public officials.

Keywords

Discrimination, Institutional trust, COVID-19, Sense of belonging, Public institutions

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DOI

https://doi.org/10.21833/ijaas.2025.04.022

Citation (APA)

Fezai, N., & Lamari, M. (2025). The impact of discrimination on trust in government institutions: A LASSO regression analysis in the Canadian context during COVID-19. International Journal of Advanced and Applied Sciences, 12(4), 200–212. https://doi.org/10.21833/ijaas.2025.04.022