US media mention Asian-named scientists less often – Asia Times

One Chinese national recently submitted a petition to the US Citizenship and Immigration Services to become a permanent resident, believing that his prospects were great. As an accomplished scientist he figured that information articles covering his study, in top media outlets including The New York Times, would show his “extraordinary ability” in the sciences, when called for by the EB- 1A visa requirements.

However, when the immigration officers rejected his petition, they discovered that his name did n’t appear anywhere in the news articles. His significant contribution to the work was not immediately demonstrated by media coverage of a paper he co-authored.

As this scientist’s close friend, I felt awful for him because I knew how far he had dedicated to the job. He also started the plan, as one of his PhD thesis chapters. However, as a scientist who researches issues relating to technological innovation, I understand the perspective of immigration officers because research is extremely conducted collaboratively, so it’s difficult to know what individual contributions are if a news article only mentions study findings.

What factors do editors have to consider when choosing which experts to have in their news stories, according to my colleagues Misha Teplitskiy and David Jurgens?

For a scientist whose name is or is n’t mentioned in journalistic coverage of their work, there is a lot at stake. News advertising are crucial in educating the public about new scientific discoveries. The visibility of a certain study is boosted by the work’s protection and the institutions ‘ people. The breadth and breadth of coverage then determines how well the public perceives who is conducting great technology. In some cases, as my brother’s story suggests, specific jobs can get affected.

Do experts ‘ cultural names, such as race or culture, perform a role in this process?

This query has a difficult truth. Given the serious marginalization of minorities in US mainstream media, cultural bias may exist on the one hand. On the other hand, science media is renowned for its high caliber of monitoring. We made the decision to use large-scale empirical data to check this problem in a systematic manner.

Chinese, Egyptian names received least policy

My colleagues and I analyzed 223, 587 media stories from 2011- 2019 from 288 U. S. media outlets reporting on 100, 486 academic papers sourced from Altmetric.com, a site that monitors website posts about analysis papers. For each paper, we focused on authors with the highest chance of being mentioned: the first author, last author and other designated corresponding authors. We determined how frequently the authors appeared in news articles about their research.

We derived perceived ethnicity from authors ‘ names using an algorithm with 78 % reported accuracy. In the absence of scientists ‘ self-reported information, we figured journalists might rely on these cues. We compared the average mention rates between nine broad ethnic groups and those who have Anglo names, such as John Brown or Emily Taylor, as the main focus.

Because many African Americans have Anglo names, such as Michael Jackson, our method does not distinguish black from white names. Because we wanted to concentrate on perceived identity, this design still has meaning.

We discovered that 40 % of the time a scientist had to be named in a news article was overall. However, authors with minorities ‘ names had significantly lower rates of mention than those with Anglo-names. Authors with East Asian and African names were typically mentioned or quoted in about 15 % less of the time in US science media than those with Anglo names, which was most pronounced.

Scientists ‘ coverage in US news is influenced by their alleged ethnicity.

Scientists with names associated with minority ethnicities are less likely than scientists with anglo names to be named or quoted in American media reports on their research.

Chinese

−5.97%

African

−5.81%

Non- Chinese East Asian

−4.34%

Southern European

−2.2%

Western &amp, Northern European

−1.16%

Indian

−0.18%

Eastern European

−0.15%

Middle Eastern

0.25%

Researchers controlled for corresponding author status, affiliation rank and location, authorship position, author rank and popularity, last name complexity, abstract readability, team size, research topics, as well as year of coverage, article length, and journalist’s demographics.

This association is consistent even after accounting for factors such as geographical location, corresponding author status, authorship position, affiliation rank, author prestige, research topics, journal impact and story length.

And it was distributed to a range of different media outlets, including those with science and technology-focused content, press release publishers, and news organizations with general interest.

rhetorical choices and grammatical considerations

Our results do n’t directly imply media bias. So what’s going on?

First and foremost, the lack of scientific names with East Asian and African names may be a result of the pragmatic difficulties that US-based journalists face in interviewing them. Factors like time zone differences for researchers based overseas and actual or perceived English fluency may be at play as a journalist works behind schedule to produce the story.

We focused on researchers with affiliations with American institutions to isolate these elements. Among US- based researchers, pragmatic difficulties should be minimized because they’re in the same geographic region as the journalists and they’re likely to be proficient in English, at least in writing. Given that US institutions are increasingly paying a premium to media attention, these scientists would presumably be just as likely to respond to journalists ‘ requests for interviews.

Even when we looked just at US institutions, we found significant disparities in mentions of and quotations from non- Anglo- named authors, albeit slightly reduced. In particular, East Asian- and African- named authors again experience a 4 to 5 percentage- point drop in mention rates compared with their Anglo- named counterparts. This finding suggests that while some disparities can be explained by pragmatic factors, not all of them can be explained.

We discovered that journalists were also more likely to use institutional affiliations to refer to researchers who had been given the names of African and East Asians, such as those who wrote about “researchers from the University of Michigan.” This institution substitution effect highlights a potential bias in media representation, where authors who have minority names may be perceived as less authoritative or deserving of formal recognition.

Reflecting a globalized enterprise

How accurately and thoroughly researchers are described in stories, whether they are named by name, or how much their contributions are highlighted through quotes, affects the depth of science news coverage. Our study emphasizes the importance of equitable representation in shaping public discourse and fostering diversity in the scientific community as science becomes more and more globalized with English as its primary language.

While our focus was on the breadth of coverage with regard to name credits, we believe that disparities are even greater at a later stage of scientific dissemination, when journalists are choosing which research papers to report on. Understanding these disparities is challenging because of decades or even centuries of bias embedded in the entire science production pipeline, including who receives funding for their research, who receives top journals to publish, and who is represented in the scientific workforce itself.

A process with a number of inequities built in is being picked by journalists at a later stage. Therefore, addressing the disparities in the media representation of scientists is only one way to promote equality and inclusivity in science. However, it makes a significant step toward more equitable distribution of innovative scientific knowledge to the general public.

Hao Peng is a postdoctoral fellow at Northwestern University in computational social science.

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