Target's Diversity Efforts Are Rankling Conservatives Again
- Bias Rating
-8% Center
- Reliability
55% ReliableFair
- Policy Leaning
-2% Center
- Politician Portrayal
26% Negative
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-100%
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100%
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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
Sentence | Sentiment | Bias |
---|---|---|
"Just a week after the Supreme Court ruling to ban affirmative action in college admissions, Republican Senator Tom Cotton of Arkansas urged Target Corp. to end its efforts to racially diversify its workforce and vendor network." | Negative | -2% Liberal |
"Just a week after the Supreme Court ruling to ban affirmative action in college admissions, Republican Senator Tom Cotton of Arkansas urged Target Corp. to end its efforts to racially diversify its workforce and vendor network." | Negative | -4% Liberal |
"Whatever side you fall on with this issue, you can't dispute that retail relies on workers of color, and attempts by lawmakers such as Cotton to end practices to attract those workers would leave stores even more desperate than they already are to find employees while further limiting one of the few career paths available to people of color." | Negative | -20% Liberal |
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
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Contributing sentiments towards policy:
49% : Just a week after the Supreme Court ruling to ban affirmative action in college admissions, Republican Senator Tom Cotton of Arkansas urged Target Corp. to end its efforts to racially diversify its workforce and vendor network.*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.