Why we should care that election officials are quitting in droves
- Bias Rating
-2% Center
- Reliability
30% ReliableFair
- Policy Leaning
10% Center
- Politician Portrayal
-24% 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
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- Conservative
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
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Contributing sentiments towards policy:
50% : It requires, among myriad responsibilities, learning how to operate specialized voting machines, combating cybersecurity threats and, increasingly, venturing out in public -- to town hall meetings, election seminars and other venues -- to explain how election operations work.48% : He said the group would like to see Congress pass "anti-doxing legislation" that would "help election officials keep sensitive personal information" -- like their home address -- "from public disclosure.
42% : In California, legislators passed a bill to extend the law protecting election officials from harassment and interference to cover staff members, temporary employees and poll workers.
35% : In other words, Republicans who spread the big lie about massive fraud and a stolen 2020 election received significantly less support -- in races for secretary of state, governor and Congress -- than Republicans who refused to traffic in such nuttiness.
*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.