
Canceling Student Debt Won't Fix the Real Injustice in Higher Education
- Bias Rating
- Reliability
N/AN/A
- Policy Leaning
-6% Center
- Politician Portrayal
-61% Negative
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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
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- Conservative
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
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Contributing sentiments towards policy:
59% : The concept of a social safety net for the desperate and most disadvantaged never envisioned five-figure transfer payments to those who possess the most sociological, professional, and economic leverage in society.57% : But what it really does is reveal the fact that this is a transfer payment for those of higher earnings, and higher earning capacity, which last time I checked was one of the main reasons people are told they will benefit from a college education.
54% : Much has been written about the regressive nature of "canceling" student debt -- of how the benefits in doing this accrue to the least unemployed and best compensated members of society.
47% : The right solution is not to replace student debt cancellation with auto loan or credit card debt cancellation, but of course, if the real agenda was a financial benefit to the lowest-tier wage earners, that is exactly where the policymakers would start.
45% : They do not always act morally or responsibly, but they can be forgiven for assuming that when a $400 billion cancellation of student debt for good wage earners takes place, a pretty large cancellation of credit card debt for poor wage earners may be next.
41% : The pending "cancellation" of student debt for those under a certain income limit speaks to this fatal flaw of the policy: that it benefits higher wage earners and is substantially paid by lower wage earners.
*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.