Counter Punch Article RatingThe Crisis in the Teamsters
- Bias Rating
10% Center
- Reliability
65% ReliableFair
- Policy Leaning
10% Center
- Politician Portrayal
-54% Negative
Continue For Free
Create your free account to see the in-depth bias analytics and more.
Continue
Continue
By creating an account, you agree to our Terms and Privacy Policy, and subscribe to email updates. Already a member: Log inBias 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
-8% Negative
- 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:
62% : Meanwhile, on the same day the Teamsters leadership met with Trump and allowed to hold a press conference in the Teamsters International headquarters afterward.40% : Palmer and possibly one other GEB member voted against O'Brien's proposal to donate $42,000 to the RNC shortly after his meeting with Trump.
26% : The dalliance with Trump and other far right notables along with the revelation of the racial discrimination lawsuit will not be easily swept under the rug, and maybe the beginning of prolonged political battle in the Teamsters.
9% : Palmer, an International Vice-President from Texas, is the sole member of the union's General Executive Board who publicly broke with O'Brien over meeting Trump privately, and then with O'Brien's demand that the entire GEB meet with Trump.
*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.