Why make it harder for some people to vote?
- Bias Rating
6% Center
- Reliability
35% ReliableFair
- Policy Leaning
10% Center
- Politician Portrayal
-35% Negative
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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
26% Positive
- Liberal
- Conservative
Sentence | Sentiment | Bias |
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
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Contributing sentiments towards policy:
58% : Until the court's shocking 2013 Shelby County v. Holder decision, states and counties with histories of racial discrimination were required to get approval from the Justice Department -- known as "preclearance" -- for redistricting or changes to voting laws.49% : The techniques include reducing the number of polling places in Black precincts, erecting barriers to voter registration, wantonly purging voter rolls, changing the rules for absentee ballots, slashing the number of drop boxes and passing voter ID laws with the pretext of preventing voter fraud, a rare occurrence that MAGA Republicans have become hysterical about.
49% : ""White racial resentment," it's worth noting, is a metric developed in the 1980s by political scientists Donald Kinder and Lynn Sanders for the American National Election Studies.
37% : Freed from federal oversight, states such as Georgia, Alabama, Texas, Mississippi and South Carolina have gone to town, enacting dozens of new restrictions in a cynical effort to make it more difficult for Black, brown and Indigenous voters and college students, all of whom lean Democratic, to cast ballots.
29% : "And study after study has shown that people who voted for Donald Trump had higher levels of racial resentment than those who did not."Until about 2008, white Republicans and Democrats demonstrated similar rates of racial resentment.
*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.