The American Conservative Article RatingHow Mass Mail-In Voting Changes Everything
- Bias Rating
30% Somewhat Conservative
- Reliability
65% ReliableFair
- Policy Leaning
52% Medium Conservative
- Politician Portrayal
-24% 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
15% Positive
- 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:
45% : States like Tennessee and Texas, which limit the use of mail-in ballots, greatly reduce the impact of Democrats' mail-in ballot mobilization efforts on elections.29% : As Texas Attorney General Ken Paxton suggested in a recent interview with Tucker Carlson, Donald Trump was "one lawsuit away" from losing Texas in 2020, as Democratic lawyers tried to open the state up to mass mail-in voting.
26% : If Paxton had not been successful in countering attempts by Democrats to send unsolicited absentee ballot applications to every voter, and install private ballot drop boxes in the heavily Democratic Texas counties of Harris (Houston), and Travis (Austin) in 2020, it is likely that Trump would have lost the state.
*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.