Author Mentions in Science News Reveal Widespread Disparities Across Name-inferred Ethnicities

TL;DR

The paper analyzes whether name-inferred ethnicity affects how scientists are credited in science news, treating this as a second-stage quality issue after a paper is selected for coverage. Using a dataset of $223{,}587$ news stories from $288$ U.S.-based outlets covering $100{,}486$ papers (with $276{,}202$ story–paper mentions) and a mixed-effects logistic regression framework on $524{,}052$ (story, paper, author) observations, the authors infer ethnicity from names via Ethnea and control for numerous factors with random effects for venues and outlets. They find substantial disparities: compared with Anglo-named authors, minority-ethnicity names—especially East Asian and African—are less likely to be mentioned by name, with average marginal effects of $1.2$ to $6.0$ percentage points lower against a $41.2\%$ baseline, and no robust gender effect when fields are controlled. These disparities persist for U.S.-based authors, manifest across three mention types (name mentions, quotes, institution substitutions), and across outlet types, though the magnitude varies by outlet. The authors discuss pragmatic and rhetorical mechanisms, acknowledge limitations, and highlight implications for science policy and journalism practice, calling for broader, cross-country research to address potential cumulative effects on representation and careers.

Abstract

Media outlets play a key role in spreading scientific knowledge to the general public and raising the profile of researchers among their peers. Yet, how journalists choose to present researchers in their stories is poorly understood. Using a comprehensive dataset of 223,587 news stories from 288 U.S. outlets reporting on 100,486 research papers across all areas of science, we investigate if the authors' ethnicities, as inferred from names, are associated with whether journalists explicitly mention them by name. By focusing on research papers news outlets chose to cover, our analysis reduces concerns that differences in name mentions are driven by differences in research quality or newsworthiness. We find substantial disparities in name mention rates across ethnically-distinctive names. Researchers with non-Anglo names, especially those with East Asian and African names, are significantly less likely to be mentioned in news stories covering their research, even when comparing stories from a particular news outlet reporting on publications in a particular scientific venue on a particular research topic. The disparities are not fully explained by authors' affiliation locations, suggesting that pragmatic factors such as difficulties in scheduling interviews play only a partial role. Furthermore, among U.S.-based authors, journalists more often use authors' institutions instead of names when referring to non-Anglo-named authors, suggesting that journalists' rhetorical choices are also key. Overall, this study finds evidence of ethnic disparities in how researchers are described in the media coverage of their research, likely affecting thousands of non-Anglo-named scholars in our data alone.

Figures (4)

• Figure 1: The average marginal effects of author's gender and ethnicity on the probability of being mentioned by name in science news reporting their research. Estimations are based on our full model (Model 5) fitted to all 524,052 observations in our data. Authors with names associated with minority ethnicities, especially East Asian and African names, are much less likely to be mentioned than Anglo-named authors after controlling for corresponding author status, affiliation rank and location, authorship position, author rank and popularity, last name complexity, abstract readability, team size, research topics, and news features such as year of coverage, article length, and journalist's demographics, as well as random effects for publication venues and news outlets. Colors are proportional to absolute probability changes (legend is shown vertically for space consideration). Woman is colored as blue to reflect its difference from ethnicity identities. The error bars indicate 95% bootstrapped confidence intervals.
• Figure 2: U.S.-based authors with minority-ethnicity names are less likely to be mentioned by name (a) or quoted (b), and are more likely to be substituted by their institution (c). The average marginal effects are estimated based on our finest model (Model 5) fitted to 317,626 observations where the author is from U.S.-based institutions. A negative (positive) marginal effect indicates a decrease (increase) in the probability of being credited compared to authors with Man (for gender) or Anglo (for ethnicity) names. The colors are proportional to the absolute probability changes. Woman is colored as blue to reflect its difference from ethnicity identities. The error bars indicate 95% bootstrapped confidence intervals.
• Figure 3: Ethnic disparities in mention rates are consistent across three types of news outlets. The similar sizes of absolute disparities in three outlet types reflect starkly different magnitude of relative effects, as the average mention rates in Press Releases, Science & Technology, and General News outlets are 63.5%, 41.9%, and 24.2%, respectively. In particular, the 6-8 percentage points drop in mention rates for Chinese and African named scholars reduces nearly one third of their expected media representation in General News outlets. We fitted a separate model (Model 5) to the subset of all observations in each type of outlet. The colors are proportional to the absolute probability changes. Error bars represent 95% bootstrapped confidence intervals.
• Figure 4: Average marginal effects on the mention probability for a one-unit increase in the mention year variable for each gender (blue) and ethnicity (red). A separate model was fitted using all observations for each demographic group. The African ethnicity is not shown due to insufficient data for fitting the model. Error bars show 95% bootstrapped confidence intervals.