
Affirmative Action Cases Could Threaten Employer DEI Initiatives
- Bias Rating
-2% Center
- Reliability
20% ReliableLimited
- Policy Leaning
-2% Center
- Politician Portrayal
N/A
Continue For Free
Create your free account to see the in-depth bias analytics and more.
Continue
Continue
By creating an account, you agree to our Terms and Privacy Policy, and subscribe to email updates. Already a member: Log inBias Score Analysis
The A.I. bias rating includes policy and politician portrayal leanings based on the author’s tone found in the article using machine learning. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral.
Sentiments
N/A
- Liberal
- Conservative
Sentence | Sentiment | Bias |
---|---|---|
Unlock this feature by upgrading to the Pro plan. |
Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
Extremely
Liberal
Very
Liberal
Moderately
Liberal
Somewhat Liberal
Center
Somewhat Conservative
Moderately
Conservative
Very
Conservative
Extremely
Conservative
-100%
Liberal
100%
Conservative

Contributing sentiments towards policy:
58% : The US Supreme Court is poised to rule on two cases challenging the use of affirmative action in college admissions at Harvard University and University of North Carolina.54% : Unlike affirmative action that uses protected class membership as a factor in decision-making, DEI programs in the employment context are policies and practices designed to ensure equal opportunities and outreach to certain underrepresented groups in the workforce.
48% : The court's opinion could indicate that race-conscious decisions aimed at remedying historical imbalances are either no longer necessary -- due to the passage of time since the initial implementation of affirmative action -- or lead to undesirable outcomes.
42% : Given these developments, employers should consider reviewing their DEI and affirmative action efforts closely and consider measures to mitigate potential risk.
*Our bias meter rating uses data science including sentiment analysis, machine learning and our proprietary algorithm for determining biases in news articles. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral. The rating is an independent analysis and is not affiliated nor sponsored by the news source or any other organization.