The Failures of the Health Insurance System
- Bias Rating
- Reliability
55% ReliableAverage
- Policy Leaning
-28% Somewhat Left
- Politician Portrayal
61% Positive
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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
3% Positive
- Liberal
- Conservative
Sentence | Sentiment | Bias |
---|---|---|
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
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-100%
Liberal
100%
Conservative

Contributing sentiments towards policy:
47% : Free public education, the abolition of slavery, labor laws, anti-discrimination laws and many other forward-looking policies began at the state level.44% : It turns out that not-for-profit systems, like Medicare or Medicaid, and universal health care systems, like those in each Canadian province, are often neither better nor worse than the for-profit offering.
42% : To the Editor: Re "Why I Quit My Job as a Health Insurance Executive," by Wendell Potter (Opinion guest essay, Dec. 20): The problems with private health coverage are not things that marginal changes can fix.
35% : Len DiSesa Dresher, Pa. Making Polluters Pay To the Editor: Re "New York Law Makes Polluters Pay on Climate" (front page, Dec. 27): One billion tons of pollution globally over the past 24 years is a very big mess that fossil fuel companies have made.
*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.