Why the race and gender politics of White Dudes for Harris failed
- Bias Rating
46% Medium Conservative
- Reliability
75% ReliableGood
- Policy Leaning
70% Medium Conservative
- Politician Portrayal
-43% 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
21% Positive
- Liberal
- Conservative
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
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Contributing sentiments towards policy:
60% : In the end Trump won the popular vote and made gains in nearly every demographic.51% : When she seemed to be losing potential votes from black men, her campaign rolled out a series of initiatives billed as targeting black male voters specifically: loans for business creation, a plan to protect cryptocurrency assets, and federal legalization of marijuana.
50% : Meanwhile, Trump made significant inroads among Hispanic voters, especially men.
49% : Before the election, Democrat admakers had evidence that narrowly targeted messages weren't working against Trump: Future Forward, a Democratic Party-aligned super PAC that specializes in data-driven ad targeting, ranked hundreds of ads and found that more general appeals worked best.
22% : How could such a person possibly appeal to women and minorities?And yet: Abortion rights did not prove a surefire winner with women voters -- millions voted for both abortion rights ballot measures and Trump.
21% : And while Trump himself was often an erratic messenger, going on long, wild tangents during his many sprawling speeches, his campaign apparatus focused relentlessly on inflation and other core economic issues that appealed to everyone.
17% : Democrats spent much of the campaign attacking Trump as harmful to women and minorities.
*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.