Lies caused the Social Security crisis. But is it too late to undo the damage?
- Bias Rating
10% Center
- Reliability
30% ReliableFair
- Policy Leaning
14% Somewhat Conservative
- Politician Portrayal
-2% 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
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- Conservative
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
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-100%
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Contributing sentiments towards policy:
59% : Yet Social Security has been invested 100% in Treasury bonds for its entire existence.56% : In the latter case, Bush wanted to allow Social Security to invest in stocks only as part of a complex program to "partially privatize" the program and create individual accounts.
54% : This has given Uncle Sam access to a huge, secure and effectively secret pool of tax money to spend.
50% : Probably the most surreal objection to letting Social Security invest in the stock market is the claim that this would politicize the stock market and give politicians power to pick the stocks of companies they liked.
48% : Social Security no longer has a sizable trust fund to invest."
47% : But the twist in the knife is that today, when political opinion is at last waking up to the obvious case for holding stocks in Social Security, it may already be too late, they add.
47% : Nor do they mention the obvious point, namely that the same people who have fought to keep Social Security out of stocks keep large chunks of their own retirement savings in stocks.
43% : Especially in the wake of the Greenspan Commission in the early 1980s, which "rescued" Social Security by raising taxes and cutting benefits -- and left all the money in Treasurys, where it could help finance Ronald Reagan's budget deficits.
*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.