Reparations debate reflects "unfinished global injustice' -- Prof Akwasi P Osei
- Bias Rating
- Reliability
35% ReliableAverage
- Policy Leaning
-4% Center
- Politician Portrayal
N/A
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.
Log In
Log in to your account to see the in-depth bias analytics and more.
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
-33% 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:
58% : The professor concluded that the UN resolution marks an important step in a long-running global conversation on justice, accountability, and the legacy of slavery.52% : " The professor pointed to divisions in the UN vote -- where over 120 countries supported the resolution while major powers such as United States and United Kingdom opposed or abstained -- as evidence of competing interests.
42% : Speaking on the Asaase Breakfast Show on Friday (27 March), the professor of history and political science at Delaware State University said the recent United Nations resolution declaring slavery a grave crime against humanity represents a culmination of decades of advocacy rather than a new shift.
*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.