Making FEMA's Emergency Management Great Again
- Bias Rating
30% Somewhat Conservative
- Reliability
75% ReliableGood
- Policy Leaning
62% Medium Conservative
- Politician Portrayal
-18% Negative
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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
-1% Negative
- Liberal
- Conservative
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
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Contributing sentiments towards policy:
56% : Trump is right on two counts: sometimes it's necessary to start fresh because otherwise there are too many entrenched interests and egos, and sometimes it's good to create an independent body to ensure objective evaluations and appropriate consequences.51% : Trump correctly sees the need for federal agencies to refocus on their core missions, reduce mission creep and redundancy, and be funded appropriately.
48% : But we were waiting, based in part on the Robert T. Stafford Disaster Relief and Emergency Assistance Act, (commonly known as the Stafford Act), for the state to ask.
46% : Problems arise when the local, county/parish, or state is reluctant to ask for help, which happens more often than you might think, for a range of psychological and political reasons.
42% : Unlike most other countries, which tend to take a much more top-down approach, in the United States, we already proceed from the assumption that disasters are initially a local issue, to be dealt with locally -- the approach Trump is now advocating for as new.
37% : "This is probably one of the best examples of it not working," Trump told reporters, of FEMA's efforts in North Carolina.
18% : Trump shouldn't "throw out the concept of a federal disaster management office with the stormwater," but reform or rebuild FEMA into the world-class emergency management agency that it can, and must, be.
*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.