NPR84%

One by one, U.S. civil rights agency dismantles tools to fight discrimination 17%

By Andrea Hsu0%

6/1/2026, 9:00:00 AM

BS Summary: This article contains 29 faulty reasoning types, including False Dilemma, Confirmation Bias, and Appeal to Authority, with Negativity Bias as the most egregious example at 14.9% saturation with 247 hits. Analysis detected 1,964 faulty-reasoning hits from 1,655 analyzed words, generating a BS Score of 32.4% and a BS Rank of 17% (18,289 of 21,887 articles). This article is better (less manipulative) than 83.60% of the article peer group.

In 1966, the newly-established Equal Employment Opportunity Commission issued a rule to tackle entrenched discrimination on the job. 
Every year, companies with a hundred or more workers would turn over to the government information about the race, ethnicity, sex and job categories of their employees. 
This EEO-1 data, as it's known, has helped the federal agency figure out where people of color and women are not getting hired or promoted. 
Over decades, the EEOC's work has led to settlements worth billions. 
Now, as part of a realignment of civil rights enforcement under President Trump, the EEOC is seeking to end its annual data collection while also getting rid of a 1979 regulation that allowed employers to take certain steps to address race and gender imbalances revealed by the data. 
Together, the moves would mark an about-face in the civil rights agency's efforts to fulfill its mission. 
Andrea Lucas, the Trump-appointed chair of the EEOC, did not respond to NPR's questions about the two proposals, which have been submitted to the White House for review. 
But in interviews and public remarks, Lucas has repeatedly warned that programs or policies aimed at helping specific groups, such as Black people or women, are unlawful under Title VII of the Civil Rights Act of 1964 if they exclude others. 
"Regardless of what has happened before, the way to stop discriminating based on race is to stop discriminating based on race. 
The end. 
Full stop," Lucas said at the Fortune Workplace Innovation Summit earlier this month. 
"I think that that's a more beautiful vision of our country, and I think it's consistent with the text of the statute." 
A roadmap for addressing discrimination 
The 1979 regulation the EEOC seeks to rescind was issued with this very dilemma in mind: Can a company remedy discrimination by giving special consideration to those who were deprived of opportunities in the past? 
The answer back then was yes. 
The agency gave the go-ahead for mentoring programs and even hiring targets. 
"The EEOC says you can take some of these voluntary efforts, even though they will be race- or gender-conscious," says Chai Feldblum, who served on the commission during the Obama and first Trump administrations. 
"This is the EEOC giving employers the roadmap of how they can take race and gender into account in a positive way and not violate the law." 
The guidelines, issued in January 1979, made clear that companies first had to document a problem, and then come up with a reasonable and time-limited plan for how to increase the number of minorities or women in their ranks. 
Five months later, the Supreme Court embraced that roadmap. 
In a 5-2 decision known as Weber, the court found that an affirmative action plan to remedy past discrimination was lawful provided it did not "unnecessarily trammel the interests of white employees" and that it was temporary. 
In 1987, the court issued another decision, known as Johnson, extending protection to efforts aimed at helping women. 
Now known as the Weber-Johnson standard, it's still the law regardless of what happens with the EEOC's 1979 regulation, says Feldblum. 
But for how long, she's not sure. 
"I think the Supreme Court is just waiting for a case that might allow them to overturn those two important cases," she says. 
How data has helped root out discrimination 
The more imminent change, assuming the EEOC's proposals go forward, is the demise of the agency's annual collection of employee demographics. 
Usually, the data collection begins in late spring. 
So far this year, there's been no word of it. 
Since the 1960s, the EEOC has recovered billions of dollars for workers who have suffered discrimination on the job, and in many cases, EEO-1 data played a key role. 
"It's one of the first things that you can look at as you're trying to learn more," says Karla Gilbride, who served as the EEOC's general counsel during the Biden administration. 
Protecting U.S. workers from unlawful discrimination  already a hard task  could become significantly harder if the government no longer has that data within arm's reach, Gilbride says. 
Having to subpoena data would make enforcement far more laborious and less efficient. 
A lawsuit against Bass Pro Shops 
Consider the lawsuit against Bass Pro Shops, first filed in 2011. 
The EEOC alleged the company, formally known as Bass Pro Outdoor World, discriminated against Black and Hispanic job applicants by not hiring them  not just at one store, but across the country, even in places with sizable Black and Hispanic populations. 
"Store by store by store, sort of the same idea, where you had areas that had a significant number of Blacks and Latinos, and either zero or very few at the stores," says David Lopez, who was the EEOC's general counsel at the time and now leads the Civil Rights, Migration and Workplace Law Initiative at Arizona State University. 
The EEOC saw that pattern because it had Bass Pro's demographic data on file. 
Government investigators could easily compare the outdoor gear shop to other retailers in the same counties. 
They could also compare Bass Pro's workforce to the available pool of workers in the surrounding areas. 
While the data by itself could not prove discrimination, Lopez says it was a green light to agency investigators to dig further. 
"Because they had a reason to investigate, they were able to discover that there were managerial comments that were reflective of discriminatory animus, that they were looking for a certain type of person," says Lopez. 
Someone who was white, according to the government's complaint. 
Bass Pro called the allegations "threadbare" and accused the government of merely relying on "a handful of isolated incidents of alleged inappropriate behavior." 
EEOC investigators later bolstered their case, identifying implicated managers and job applicants by name and compiling a list of dozens of Bass Pro stores with a low representation of Black and Hispanic employees. 
Finally, in 2017, the company settled for $10.5 million. 
Bass Pro did not admit to any wrongdoing, but agreed to appoint a diversity director and to make good-faith efforts to recruit and hire non-white candidates. 
Lopez considered the settlement a big win, one of many he oversaw in his time at the EEOC that were built on data. 
"You can have a hunch, but there's nothing like the cold, hard numbers," he says. 
Agency chair says data has been misused 
Early indications of the EEOC's plan to stop gathering data came a year ago. 
In announcing the opening of the 2025 data collection period, Lucas posted a message warning employers of their obligations under federal civil rights law. 
"You must not use the information collected and reported in your organization's EEO-1 Component 1 report to justify treating employees differently based on their race, sex, or other protected characteristic," she wrote. 
In an interview with NPR earlier this year, Lucas explained her missive. 
She said a number of companies have been misusing the data  including in ways that have hurt white people and men. 
Lucas believes the only people who should know the gender and race of a company's employees are its lawyers and human resources staff. 
Instead, after the 2020 murder of George Floyd by a white police officer, a number of companies published their demographic data as part of public commitments to address the lack of diversity within their ranks. 
Subsequently, she contends, companies began making decisions about whom to hire, promote and interview for jobs based on sex or race, noting some even gave hiring managers financial incentives to hit diversity targets. 
That use of demographic data crosses the line, she says. 
"All it has to do is motivate  in whole or in part  your decision making, and you're into unlawful territory." 
Lucas declined to single out any company by name, citing the confidentiality of agency investigations. 
But according to court documents, the EEOC has accused Nike and The New York Times of discrimination against white employees and job applicants. 
The two companies are among many that published their demographic data along with their diversity-related goals for several years. 
A focus on data in select cases 
Paradoxically, Lucas has at times talked up the importance of data. 
"There is no other way to protect victims of harassment and discrimination unless you collect information about them," she said while speaking in April at a conference at Harvard organized by the Brandeis Center, an independent civil rights organization. 
In that instance, she was defending the EEOC's subpoena, requiring the University of Pennsylvania to turn over employee information that the agency doesn't routinely collect: the names, addresses and phone numbers of Jewish employees who may have witnessed antisemitic acts on campus. 
The university has, so far, refused to comply with the subpoena, noting in court filings that it echoes terrifying periods of history for Jewish communities. 
"Driving a car without a dashboard" 
The profound changes underway at the EEOC have kept David Cohen busy. 
The president of the management consulting firm DCI Consulting has fielded many calls from confused clients, wondering whether the work they've been doing to promote equal opportunity should continue. 
For now, he's telling clients that keeping track of their employee demographics is a smart business move, whether the government requires it or not. 
Without it, he says, a company has no way of knowing if it has a problem  whether it's recruiting from too narrow a pool, or has a bad manager somewhere, or is screening out qualified candidates for no good reason. 
"It's like you're driving a car without a dashboard. 
You have no idea what's going [on]. 
Am I speeding? 
Am I not speeding? 
Is my check-engine light on?" 
he says. 
"You have nothing." 
He's been reminding clients that while priorities have shifted at the EEOC, federal civil rights laws haven't changed. 
"Stay within the law, and you will be okay," he says. 
Article reasoning-pattern comparisonThis article: 8.9%Andrea Hsu: 2.8%Goats and Soda (NPR): 3.4%Confirmation Bias8.9%This article: 2.1%Andrea Hsu: 1.2%Goats and Soda (NPR): 1.6%Anchoring Bias2.1%This article: 7.2%Andrea Hsu: 2.8%Goats and Soda (NPR): 3.8%Availability Heuristic7.2%This article: 3.6%Andrea Hsu: 2.2%Goats and Soda (NPR): 1.2%Representativeness Heuristic3.6%This article: 0.9%Andrea Hsu: 0.5%Goats and Soda (NPR): 0.8%Hindsight Bias0.9%This article: 7.6%Andrea Hsu: 1.3%Goats and Soda (NPR): 2.4%Overconfidence Bias7.6%This article: 3.3%Andrea Hsu: 12.6%Goats and Soda (NPR): 11.1%Framing Effect3.3%This article: 4.2%Andrea Hsu: 1.3%Goats and Soda (NPR): 1.2%Loss Aversion4.2%This article: 2.1%Andrea Hsu: 1.1%Goats and Soda (NPR): 1.1%Status Quo Bias2.1%This article: 0.0%Andrea Hsu: 0.0%Goats and Soda (NPR): 0.2%Sunk Cost Effect0.0%This article: 3.9%Andrea Hsu: 1.7%Goats and Soda (NPR): 3.4%Optimism Bias3.9%This article: 2.2%Andrea Hsu: 2.2%Goats and Soda (NPR): 2.3%Pessimism Bias2.2%This article: 14.9%Andrea Hsu: 7.0%Goats and Soda (NPR): 11.3%Negativity Bias14.9%This article: 1.4%Andrea Hsu: 0.5%Goats and Soda (NPR): 2.3%Self-Serving Bias1.4%This article: 0.0%Andrea Hsu: 2.0%Goats and Soda (NPR): 1.1%Fundamental Attribution Error0.0%This article: 0.0%Andrea Hsu: 0.4%Goats and Soda (NPR): 0.3%Actor-Observer Bias0.0%This article: 0.0%Andrea Hsu: 1.4%Goats and Soda (NPR): 2.3%In-Group Bias0.0%This article: 0.0%Andrea Hsu: 0.4%Goats and Soda (NPR): 1.2%Out-Group Homogeneity Bias0.0%This article: 5.1%Andrea Hsu: 2.1%Goats and Soda (NPR): 2.8%Halo Effect5.1%This article: 0.0%Andrea Hsu: 0.0%Goats and Soda (NPR): 0.3%Horn Effect0.0%This article: 0.0%Andrea Hsu: 0.0%Goats and Soda (NPR): 0.0%Dunning-Kruger Effect0.0%This article: 4.1%Andrea Hsu: 1.5%Goats and Soda (NPR): 1.7%Recency Bias4.1%This article: 0.0%Andrea Hsu: 0.2%Goats and Soda (NPR): 0.5%Primacy Effect0.0%This article: 0.0%Andrea Hsu: 0.0%Goats and Soda (NPR): 0.1%Blind-Spot Bias0.0%This article: 0.0%Andrea Hsu: 0.4%Goats and Soda (NPR): 1.2%Ad Hominem0.0%This article: 0.0%Andrea Hsu: 0.1%Goats and Soda (NPR): 0.3%Straw Man0.0%This article: 8.0%Andrea Hsu: 4.6%Goats and Soda (NPR): 6.1%Appeal to Authority8.0%This article: 10.0%Andrea Hsu: 2.6%Goats and Soda (NPR): 1.5%False Dilemma10.0%This article: 1.3%Andrea Hsu: 2.4%Goats and Soda (NPR): 1.3%Slippery Slope1.3%This article: 0.0%Andrea Hsu: 0.1%Goats and Soda (NPR): 0.1%Circular Reasoning0.0%This article: 3.3%Andrea Hsu: 5.9%Goats and Soda (NPR): 4.4%Hasty Generalization3.3%This article: 0.0%Andrea Hsu: 0.3%Goats and Soda (NPR): 0.3%Red Herring0.0%This article: 0.0%Andrea Hsu: 0.2%Goats and Soda (NPR): 0.7%Bandwagon0.0%This article: 2.8%Andrea Hsu: 4.1%Goats and Soda (NPR): 6.6%Appeal to Emotion2.8%This article: 1.3%Andrea Hsu: 0.7%Goats and Soda (NPR): 0.9%Begging the Question1.3%This article: 7.7%Andrea Hsu: 3.1%Goats and Soda (NPR): 2.8%Post Hoc (False Cause)7.7%This article: 0.0%Andrea Hsu: 0.0%Goats and Soda (NPR): 0.2%Tu Quoque0.0%This article: 1.6%Andrea Hsu: 0.2%Goats and Soda (NPR): 0.4%Burden of Proof1.6%This article: 0.0%Andrea Hsu: 0.3%Goats and Soda (NPR): 0.2%Appeal to Nature0.0%This article: 0.0%Andrea Hsu: 0.3%Goats and Soda (NPR): 0.2%Composition/Division0.0%This article: 5.3%Andrea Hsu: 1.9%Goats and Soda (NPR): 2.8%Anecdotal5.3%This article: 0.0%Andrea Hsu: 0.1%Goats and Soda (NPR): 0.1%No True Scotsman0.0%This article: 1.1%Andrea Hsu: 1.7%Goats and Soda (NPR): 1.5%Ambiguity (Equivocation)1.1%This article: 0.0%Andrea Hsu: 0.0%Goats and Soda (NPR): 0.0%Gambler’s Fallacy0.0%This article: 0.7%Andrea Hsu: 0.1%Goats and Soda (NPR): 0.1%Middle Ground0.7%This article: 0.0%Andrea Hsu: 0.0%Goats and Soda (NPR): 0.1%Personal Incredulity0.0%This article: 0.0%Andrea Hsu: 0.1%Goats and Soda (NPR): 0.2%Special Pleading0.0%This article: 0.0%Andrea Hsu: 0.3%Goats and Soda (NPR): 0.5%Genetic Fallacy0.0%This article: 0.0%Andrea Hsu: 0.7%Goats and Soda (NPR): 1.3%Unattributed Quote0.0%This article: 0.0%Andrea Hsu: 1.2%Goats and Soda (NPR): 0.9%Quote-first Misdirection0.0%This article: 0.7%Andrea Hsu: 2.0%Goats and Soda (NPR): 3.1%Biased Writer Voice0.7%This article: 1.9%Andrea Hsu: 2.0%Goats and Soda (NPR): 1.0%Indoctrination1.9%This article: 0.0%Andrea Hsu: 2.0%Goats and Soda (NPR): 1.1%Politically Left Leaning Bias0.0%This article: 0.0%Andrea Hsu: 0.3%Goats and Soda (NPR): 0.3%Politically Right Leaning Bias0.0%This article: 1.5%Andrea Hsu: 0.2%Goats and Soda (NPR): 0.3%Attempt to Sell a Product or S…1.5%

1655 words analyzed.

Speakers

5speakers42%attributed speech959writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 12 words • 100.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 27 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 48 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 41 words • 0.0% coverageAndrea Lucas • 21 words • 0.0% coverageAndrea Lucas • 2 words • 0.0% coverageAndrea Lucas • 13 words • 0.0% coverageAndrea Lucas • 22 words • 0.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 35 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageChai Feldblum • 34 words • 0.0% coverageChai Feldblum • 27 words • 0.0% coverageWriter's voice • 39 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 37 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageChai Feldblum • 21 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageChai Feldblum • 23 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 29 words • 0.0% coverageKarla Gilbride • 31 words • 0.0% coverageKarla Gilbride • 29 words • 0.0% coverageKarla Gilbride • 13 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 42 words • 0.0% coverageDavid Lopez • 59 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageDavid Lopez • 22 words • 0.0% coverageDavid Lopez • 35 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 33 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageDavid Lopez • 23 words • 0.0% coverageDavid Lopez • 15 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageAndrea Lucas • 32 words • 100.0% coverageWriter's voice • 12 words • 0.0% coverageAndrea Lucas • 22 words • 0.0% coverageAndrea Lucas • 23 words • 0.0% coverageWriter's voice • 35 words • 0.0% coverageAndrea Lucas • 33 words • 0.0% coverageAndrea Lucas • 10 words • 0.0% coverageAndrea Lucas • 22 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageAndrea Lucas • 39 words • 0.0% coverageWriter's voice • 42 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 29 words • 0.0% coverageDavid Cohen • 24 words • 100.0% coverageDavid Cohen • 41 words • 0.0% coverageDavid Cohen • 9 words • 0.0% coverageDavid Cohen • 7 words • 0.0% coverageDavid Cohen • 3 words • 0.0% coverageDavid Cohen • 4 words • 0.0% coverageDavid Cohen • 5 words • 0.0% coverageWriter's voice • 2 words • 0.0% coverageDavid Cohen • 3 words • 0.0% coverageDavid Cohen • 18 words • 0.0% coverageDavid Cohen • 11 words • 0.0% coverage
Selected voice

David Lopez

100%flagged-word coverage
154 attributed words22% of attributed speech64% writer coverage
0%2.5%5.0%Biased Writer Voice-1.3 ptsWriter: 1.3%David Lopez: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

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