
Air Force disciplines 15 for 'lack of supervision' after massive leak of classified docs
- Bias Rating
- Reliability
35% ReliableAverage
- Policy Leaning
-10% 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.
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
-42% 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:
56% : "When there is a breach of that sacred trust, for any reason, we will act in accordance with our laws and policies to hold responsible individuals accountable," Kendall said in a statement.53% : The actions ranged from relieving personnel from their positions, including command positions, to non-judicial punishment. Col. Sean Riley, the commander of the 102 Intelligence Wing, 102 IW commander, was relieved of command and received administrative action.
52% : Enrique Dovalo, commander of the 102nd Intelligence, Surveillance and Reconnaissance Group, received administrative action for concerns with unit culture and compliance with policies and standards.
47% : Other steps the department took include improving need-to-know enforcement for electronic and hard-copy classified information, providing additional guidance physical security, increasing clarity on who is responsible for reporting suspicious behavior, and increased emphasis on cyber hygiene.
*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.