
Climate solutions and problems
- Bias Rating
- Reliability
35% ReliableAverage
- Policy Leaning
10% Center
- Politician Portrayal
N/A
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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
1% Positive
- Liberal
- Conservative
Sentence | Sentiment | Bias |
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
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-100%
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100%
Conservative

Contributing sentiments towards policy:
62% : To replace fossil fuels in electricity generation, solar and wind must replace not just coal but natural gas as well -- a big challenge.60% : William C. Evans, Germantown Catherine Rampell's discussion of fossil fuels was both interesting and informative.
55% : Her column on moving away from fossil fuels mentioned only wind and solar as the non-carbon energy sources currently available.
55% : But missing from the graph is natural-gas generation, which, although substantial even at the time of peak coal generation, has increased greatly since then, making up for a substantial fraction of the decline in coal generation.
54% : It is true and important that wind and solar generation are increasing rapidly and are about to overtake coal generation, which has been decreasing rapidly.
51% : The 792 billion kilowatt-hour increase represents replacement of about 75 percent of the decrease in coal generation, about 1,200 billion kilowatt-hours, as can be seen in Ms. Rampell's graph.
49% : We are going to need this reliable non-carbon energy source to be a member of a team of technologies to address the climate problem.
34% : However, her Jan. 3 op-ed, "Will we turn away from fossil fuels in time?," made that facility disappear.
*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.