The Unequal Challenge of Learning from Under-Informative News

Andrew Trexler

British Journal of Political Science2026https://doi.org/10.1017/s0007123425101300article
ABDC A*
Weight
0.50

Abstract

Political news consumption is highly uneven today: few people consume from news outlets directly, while many encounter news incidentally through social media and aggregators. Because outlets depend on direct consumers for revenue, they respond primarily to this core audience’s preferences. Several contemporary styles of news coverage—which emphasize partisan conflict, employ specialized jargon, engage in predictive analysis, and use clickbait language—are attractive to core consumers, but may also make news less accessible for others. In a pre-registered survey experiment ( n = 2,233), I show that, relative to a public interest style that prioritizes key information about policy and democratic norms, typical news styles weaken post-exposure recall of key news information—that is, they are under-informative. Recall penalties are especially severe for those with lower baseline political engagement, yet still affect highly engaged consumers as well. This study shows that contemporary approaches to news coverage broadly under-serve the public by inhibiting political learning.

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.1017/s0007123425101300

Or copy a formatted citation

@article{andrew2026,
  title        = {{The Unequal Challenge of Learning from Under-Informative News}},
  author       = {Andrew Trexler},
  journal      = {British Journal of Political Science},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1017/s0007123425101300},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

The Unequal Challenge of Learning from Under-Informative News

Flags are reviewed by the Arbiter methodology team within 5 business days.


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.