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Parkland CEO: What Medicaid cuts really mean for American health

  • Bias Rating
  • Reliability

    25% ReliableLimited

  • Policy Leaning

    86% Very Right

  • Politician Portrayal

    N/A

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

-42% Negative

  •   Conservative
SentenceSentimentBias
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Bias Meter

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Bias Meter

Contributing sentiments towards policy:

47% : In Texas, Medicaid covers low-income pregnant women, children, individuals with disabilities, and nursing home residents.
47% : In Texas, Medicaid covers low-income pregnant women, children, individuals with disabilities, and nursing home residents.
44% : While these changes may be worthy of debate, the policies behind them are not fraudulent, and the impact will be the loss of federal funds to support millions of people who depend on Medicaid for their health care.
43% : States must react by either raising taxes to maintain services or taking actions that will reduce access to care such as cutting Medicaid rolls, reducing services offered, or reducing provider payments.
35% : In the desire of some policymakers to support two opposing policy positions simultaneously, many of us fear that they will be deceived into accepting a simplistic explanation that such a cut will not impact the millions of beneficiaries who depend on Medicaid.
35% : What is not reasonable is to suggest that by eliminating this funding mechanism, the result will be to cut out fraud and not to cut Medicaid.
34% : Some policymakers are suggesting that these dollars can come from identifying fraud, waste and abuse without cutting Medicaid itself.

*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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