RealClearPolitics Article Rating'Tax the Rich' Mantra Is Rooted in Sociology, Not Economics | RealClearPolitics
- Bias Rating
- Reliability
N/AN/A
- Policy Leaning
40% Somewhat Right
- Politician Portrayal
14% Positive
Continue For Free
Create your free account to see the in-depth bias analytics and more.
By creating an account, you agree to our Terms and Privacy Policy, and subscribe to email updates.
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
N/A
- Liberal
- Conservative
| Sentence | Sentiment | Bias |
|---|---|---|
Unlock this feature by upgrading to the Pro plan. | ||
Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
Extremely
Liberal
Very
Liberal
Moderately
Liberal
Somewhat Liberal
Center
Somewhat Conservative
Moderately
Conservative
Very
Conservative
Extremely
Conservative
-100%
Liberal
100%
Conservative
Contributing sentiments towards policy:
59% : Alexandria Ocasio-Cortez's recent Met Gala dress sparked a renewed conversation on the perceived fairness of "the rich" paying their "fair share" in taxes.48% : Before going further, we need to consult the facts, according to the nonpartisan Congressional Budget Office: "In 2018, households in the highest quintile received 55 percent of income before transfers and taxes and paid 70 percent of federal taxes [emphasis added].
44% : Yet raising taxes in the name of reducing income inequality may actually diminish opportunities to climb the income ladder.
43% : Households in the lowest quintile received 3.8 percent of income before transfers and taxes and paid about 0.01 percent of federal taxes, on net.
42% : They wouldn't be at risk of becoming dependent on welfare if universal programs create too much dependency.
*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.
