NY Times Article Rating

Congress Approves Full Social Security Benefits for Public Sector Retirees

Dec 21, 2024 View Original Article
  • Bias Rating

    -24% Somewhat Liberal

  • Reliability

    70% ReliableGood

  • Policy Leaning

    10% Center

  • Politician Portrayal

    -37% 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

29% Positive

  •   Liberal
  •   Conservative
SentenceSentimentBias
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Bias Meter

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Bias Meter

Contributing sentiments towards policy:

60% : The vote to clear the measure was a lopsided 76 to 20, reflecting the broad popularity of an effort to allow approximately more than 2.8 million public pension recipients -- some of them teachers, firefighters and police officers -- to collect Social Security benefits at the same level as other beneficiaries.
60% : The woman's husband was a Navy veteran who paid into Social Security for 40 years, but since she received a public pension from the school system, her surviving spousal benefits through Social Security were reduced by two-thirds.
58% : "But we also have an obligation to honor our promises to ensure that Social Security is going to be there for the people who have paid into it and have earned it, and also those generations who come after.
52% : "There's so much riding on us getting this right and having the courage to fix Social Security over the next few years," he said.
50% : "Public sector retirees and their allies on Capitol Hill in both parties have pressed for the measure for decades.
38% : "Senator Thom Tillis, Republican of North Carolina, argued that a bill affecting the financial integrity of Social Security was too important to rush through at the end of the year without debate.

*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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