The author discusses the book on science and the definition of competence

Science is a qualification. The ability of scientists to conceive is far more important than a scientist being black or white, a man or a woman, and gay or straight. Right?

Not so fast, a new book says, Misconceptions Qualifications: The paradox of excellence and devotion to academic science and engineering (University of Chicago Press). The book is by two scholars of work and gender. Mary Blair-Loy Professor of Sociology at the University of California, San Diego. He is its author Competitive devotion: career and family among women executives. Erin A. Chech is an associate professor of sociology at the University of Michigan. He is its author Problems with Emotions: How Seeking perfection in the workplace encourages inequality.

Blair-Loy and Chech have studied more than 500 STEM professors at a top research university to reveal how unequal and unfair results can emerge, along with promises of objectivity and excellence. The authors see that STEM in academia harbors influential cultural beliefs that not only perpetuate mistreatment of the presented group of scientists but also hinder innovation.

They answered questions via email.

Q: How did you identify the university where you studied? Can you give any clues about it?

A: Our goal was to study a public research-intensive (R-1) university with a strong STEM program, the university’s commitment to justice and fairness, and a transparent academic staff system as much as possible. Our case university meets these criteria. There, the academic progress process goes through various levels of review including checks and balances and at each step the decisions and their arguments are made available to the professor under review. The salaries and progress levels of all the faculties of this university are made universal. If fair practice exists somewhere in academic STEM, they should be here. Nevertheless, we document how many under-prepared faculties continue to experience devaluation despite having similar productivity metrics in population groups.

In this case the size of the university and the student-faculty ratio are roughly the same as in other comparatively ranked universities in the US. A complementary analysis of data from our STEM Inclusion Study, which includes data from more than 7,000 STEM educators from four-year institutions across the country, shows that the cultural beliefs we identify suggest similarly significant similarities between STEM educators in the United States. They are more widely present in academic STEM.

Q: Is it wrong to believe that science is a qualification?

A: The belief in purposeful, meritocratic assessment is sacred in academic science and is widely shared across populations and disciplines. Most believe that they know excellence when they see it, and that scientists and administrators can identify and reward those who have made the greatest scientific contributions. Yet there are several problems with this belief. We will briefly mention four.

First, in many cases, this belief is not supported by evidence. Our case study data combines four powerful, layered sources: administrative data of all term or term-track STEM faculty members at Case University; A detailed survey on half of these faculties; In-depth interviews with 85 of them; And a database িক output with external, standardized metrics of publications and grants যা that STEM faculty and administrators consider as indicators of productivity and visibility.

Our quantitative analyzes show that there is no average difference between the division and the level of progress in the net, the productivity metrics or the time spent in research by gender, race / ethnicity or parent. Yet those who seem to be consistent with the cultural schemes of faculty excellence and dedication are more likely to be seen as excellent as the net of their productivity.

Second, we see that meritocracy therefore often serves as a norm that justifies the greater respect and resources given to some faculties (including white and Asian men and / or strong faculties) inequitably given to others, often as less excellent (proportionately black). Is seen. And Latinox men, women of all racial / ethnic backgrounds, mothers, and / or LGBTQ faculty), although they are just as productive.

We have unusually deep and extensive evidence from our case study university. Our results are consistent with many studies on the academic STEM population and help to explain the sustainable under-representation of many groups.

Third, this belief in the intellectual system distorts objective and analytical thinking that scientists are proud of. In the interview, we observed that smart, well-connected teachers are trying to explain the strong evidence of bias and discrimination in STEM by tying themselves together to maintain their belief that STEM is a qualification.

Fourth, this widely shared belief that STEM is already acting as a talent could be bad for science.

Question: Your book talks about two influential beliefs of science: schema of dedication and schema of scientific excellence. How are these schemes used to deny opportunities to women or men who are members of minority groups?

A: The devotional schema of work frames science as the claimant and deserving of single-minded obedience and frames mothers as lacking the necessary devotion. Yet we find that mothers develop the same publishing and grant metrics as men and childless women. Mothers of the same category and level of progress are underestimated and given less of their productivity. In response to this stigma, mothers often degrade their status as mothers or pass as mothers so that they are taken seriously as academic scientists and engineers.

The schema of scientific excellence is a set of characteristics that form a kind of measure, which scientists use to measure each other’s merits and excellence. The Schema of Scientific Excellence evaluates scientists who are seen by others as bright, strong, and self-promoting. White and Asian heterosexual men are often seen as possessing these qualities automatically, while the underprivileged and minority faculties do not benefit from this automatic assumption of superiority despite having their equal average productivity. Academic scientists and engineers who consider themselves more assertive and self-promoting earn on average more than others, although they do not actually produce much scientific work. Black and Latino men and women, white women, and LGBTQ faculties are worse than white and Asian heterosexual men in terms of average, respect, and professional integration, even in terms of productivity net, job level, and department.

Women’s faculties, especially black and Latin women, also face punishment of honor. Men get credit for relational skills, but women don’t. Determined “cowboys” are seen as the product of the best science, but only the majority-race men get full credit for this perseverance. Black and Latin women are underestimated for their firmness, while Asian women are marginalized for not being strong enough. And, despite the myth of their independence, majority-race men actually receive more informal advice than other junior scientists.

Scientists who are careful and employed about diversity and inclusion efforts also face punishment of honor. They are sometimes seen as very politically involved and distorted science productions. In addition, LGBTQ faculty often feel pressured to downplay their sexual identities and family life because their identities can be seen as politicizing and distorting “objective” science.

Schemes of dedication and scientific excellence are bad for scientists and bad for science. They despise caring, other creative pursuits, rest and rebirth. They evaluate individualistic, self-promoting “cowboys” and “rock stars,” but innovation often requires deeply collaborative work across departments, disciplines, generations, and different identities.

Q: Is there a bias against Asians in science?

A: Compared to the US population, Asian men are not under-represented in STEM. In our quantitative system, Asian and white men alike enjoy privileged qualifications with greater respect. However, other studies on the U.S. professional workforce have shown that Asian men are more likely to face marginalization and barriers to leadership than white men.

Asian women are under-represented in STEM compared to their proportion in the national population and we find that they are often underestimated. Previous research shows that Asian women face more pressure than white women to adhere to the rules of passive femininity and they may say that they need to bow their heads and work harder while leading others. In our study, Asian female faculties generally do not have the same benefits as Asian and white men. We see that black and Latinox women react to the feature of perseverance, while Asian women experience polarization because they are not persistent enough.

Q: What can departments, colleges and universities do about the problems you have identified?

A: Solutions should first address the structural manifestations of this cultural belief. Formal academic reviews should be systematically tracked and fully rewarded with teaching, inclusive counseling and translation work as much as it values ​​the production of the article. Further, academic culture marginalizes scientists who can offer something different than mainstream perspectives and experiences. Yet research shows that marginal scientists are most likely to add value to scientific initiatives. Therefore, academic units should be prioritized and rewarded with fair and equitable collaboration between people of different perspectives, backgrounds and experiences, which has the potential to develop the most pioneering work in research. The commitment of professors for fair, diverse and inclusive cooperation between departments and universities should be fully valued.

We identify three opportunities that are particularly timely.

First, we find that professors are often more personally committed to what they see in their discipline towards college, counseling, and diversity. It creates an opportunity for scientists to rethink their own values ​​and what they see as value in daylight in STEM.

Second, the post-epidemic period is an important time to compare with the contribution of the devotional schemer to the devaluation of mothers in STEM.

Third, Western approaches to science can learn a lot from feminist, post-colonial, and tribal approaches that provide insights into how to value attitudes, cooperation, credit-sharing, and humility in the process of creating knowledge.

STEM work has always been inherently cultural and social. It’s high time to embrace diversity and equity as an amplifier of innovation and not a threat to it.

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