Harris could get 'the highest level of evangelical support since Carter' -- here's how: pastor
- Bias Rating
10% Center
- Reliability
75% ReliableGood
- Policy Leaning
10% Center
- Politician Portrayal
-3% 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
41% Positive
- Liberal
- Conservative
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
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Contributing sentiments towards policy:
52% : "Pagitt notes "Trump beat Clinton by 3 points in Kent County in 2016," but due to Vote Common Good's election efforts, "In 2020, he lost to Biden there by 6 points, a 9-point swing."READ MORE: Christianity Today editor laments evangelicals defending Trump like 'the left in the Clinton era'Furthermore, if Democrats want to win evangelical support, the Party must take a "concerted, grassroots effort to reach these voters," Paggit says, "listen to them and bring them along on a journey to help them understand it's OK for them to let concern for the common good, and not allegiance to a political party, determine how they vote.43% : "We held voter rallies and roundtables; put up billboards juxtaposing the words of Jesus Christ with those of Trump; sent thousands of postcards to evangelical voters; and trained multiple local Democratic candidates on how to engage with faith voters," Pagitt writes.
29% : "On the trail in 2020, 2022 and this year, I've gleaned the reason many evangelical and Christian voters ultimately leave Trump: his obvious lack of kindness," Pagitt writes.
20% : "Our message to the 25% of the Kent County electorate that identified as evangelical was simple: Trump lacks kindness and it's OK not to vote for the Republican.
*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.