The Economist Article Rating

A new answer to the biggest climate conundrum, greening industry

Feb 15, 2024 View Original Article
  • Bias Rating

    50% Medium Conservative

  • Reliability

    30% ReliableFair

  • Policy Leaning

    50% Medium Conservative

  • Politician Portrayal

    N/A

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

Overall Sentiment

32% Positive

  •   Liberal
  •   Conservative
SentenceSentimentBias
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Bias Meter

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Bias Meter

Contributing sentiments towards policy:

70% : When those molecules contain carbon atoms (and a great many do -- they are a wonderfully versatile resource) those carbon atoms tend to come from fossil fuels.
55% : Like most industrial firms over the past 150 years, New Belgium burns fossil fuel to produce steam, which in its case then heats the ingredients required to make beer.
52% : Second, the standard ways of making cement and steel require carbon as an input, which means emitting carbon dioxide is unavoidable even if clean electricity were to replace the burning of fossil fuels.
50% : Electricity is for houses and light bulbs and maybe even for cars, but not for heavy industries built around burning heroic quantities of fossil fuel.
48% : The hardest industrial processes to electrify are those that require intense heat around the clock, especially if they use fossil fuels not only to generate heat but also to provide some sort of chemical necessity -- such as the carbon used in steelmaking.
38% : Addison Stark, the chief executive of AtmosZero, has explained that his firm explicitly set out to overcome managers' objections by designing its electric boiler to slot into existing factories easily and so reduce the hassles of installation.

*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.

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