AP News Article Rating

Universal health care proposal gets first test in California | AP News

Jan 12, 2022 View Original Article
  • Bias Rating

    -16% Somewhat Liberal

  • Reliability

    N/AN/A

  • Policy Leaning

    -24% Somewhat Liberal

  • Politician Portrayal

    -27% Negative

Bias Score Analysis

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

Overall Sentiment

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  •   Conservative
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Bias Meter

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Bias Meter

Contributing sentiments towards policy:

58% : Voters overwhelmingly rejected a 1994 ballot initiative that would have created a universal health care system.
57% : They hope that separating the idea of a universal health care system from the question of how to pay for it will give them a better chance of getting the bills through and eventually, getting voters to approve it.
56% : This year, Democrats in the state Assembly have filed two bills: one that would create the universal health care system and set its rules, the other would lay out how to pay for everything by raising taxes on some wealthier individuals and larger businesses.
55% : The plan for universal health care requires at least a two-thirds vote in both houses of the state Legislature.
54% : Progressives have tried for years to create a government-funded universal health care system to replace the one that relies on private insurance.
50% : State lawmakers in Vermont have tried and failed to implement their own universal health care system.
48% : Universal health care has been debated for decades in the United States, most recently during the 2020 Democratic presidential primary during the campaign of U.S. Sen. Bernie Sanders.
40% : The California Taxpayers Association, which opposes the plan, says it would raise taxes by $163 billion per year on businesses and individuals.

*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.

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