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Taking a seat, taking a side: How news media shapes covert discrimination

Lise-Lore Steeman et al.

European Journal of Communication2026https://doi.org/10.1177/02673231261422084article
ABDC B
Weight
0.50

Abstract

Understanding covert discrimination is as critical as overt discrimination in combating injustices. This study examines how news media consumption and trust shape covert discriminatory preferences. By analyzing various news media sources (television, newspapers, and social media) and various discrimination grounds, we highlight the complex relationship between factors driving covert discrimination. We use data from an online survey among 3000 Belgian adults, employing a conjoint experimental design to capture implicit bias in the seating preferences on public transport. Results show that media consumption and trust significantly moderate discriminatory preferences. Light consumers of public television news and heavy consumers of commercial television news display greater discriminatory preferences. Higher trust in public broadcasters and quality newspapers aligns with favoring individuals without visible minority traits, while lower trust correlates with preferences for overweight and transgender individuals. TikTok, X, and Instagram consumption also influences these patterns. Our findings have implications for media policy and diversity interventions.

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https://doi.org/https://doi.org/10.1177/02673231261422084

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@article{lise-lore2026,
  title        = {{Taking a seat, taking a side: How news media shapes covert discrimination}},
  author       = {Lise-Lore Steeman et al.},
  journal      = {European Journal of Communication},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/02673231261422084},
}

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Taking a seat, taking a side: How news media shapes covert discrimination

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.