
Iowa's top elections official concerned over cybersecurity funding pause
- Bias Rating
-4% Center
- Reliability
80% ReliableGood
- Policy Leaning
4% Center
- Politician Portrayal
-21% 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
23% Positive
- Liberal
- Conservative
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
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Contributing sentiments towards policy:
58% : "I personally prefer my approach, and that is one where we deal with all this at the voter registration level, rather than the day they're voting, because then we can do it in a much more user-friendly approach.53% : Krebs, who was appointed by Trump during his first term, countered Trump in 2020 after the president falsely claimed that he had won that year's election.
47% : Pate said compiling the list was necessary after his office was not granted access to a federal program that stores information about noncitizens on public assistance programs called the Systematic Alien Verification for Entitlements program, or SAVE.
40% : " Last month, the Associated Press reported the Trump administration had cut about $10 million in funding that the U.S. Cybersecurity and Infrastructure Security Agency provides to the nonprofit Center for Internet Security, which helps businesses and governments protect themselves against cyber threats. Trump also called Wednesday for the U.S. Department of Justice to launch an investigation into CISA Director Chris Krebs, according to NBC.
40% : " Pate also doubled down on his support for a slate of election-related bills making their way through both chambers of the Iowa Legislature, including House File 954, which addresses elections laws regarding voter registration, citizenship and major party status.
*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.