Data darkness in US spreads a global shadow
- Bias Rating
- Reliability40% ReliableAverage 
- Policy Leaning34% Somewhat Right 
- Politician Portrayal-56% Negative 
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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
-5% Negative
- 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%
Liberal
100%
Conservative
 
 
Contributing sentiments towards policy:
50% : "Intensification of political pressure on policy institutions...could erode hard-won public confidence in their ability to fulfill their mandates," the World Economic Outlook published Tuesday by the IMF stated.50% : Short answer: Not as bad as expected when Trump first took office, at least through September, but still adjusting, according to the IMF's WEO update that found "a significant, though not massive, impact of shifting policies on the economic outlook."
49% : What happens in America, in other words, doesn't stay in America, and global officials say being left data-blind by the shutdown over time could complicate their own policymaking and boost the risk of a mistake at a moment when countries are already adjusting to the Trump administration's efforts to remake global trade.
47% : " If the spring IMF and World Bank meetings were all about the uncertainty posed by Trump's plans for higher tariffs and rising protectionism, attention is now fixed on how companies, countries and consumers are coping with the new landscape.
44% : "Pressures on technocratic institutions mandated with data collection and dissemination could also erode the public's and markets' trust in statistics from official sources, significantly complicating the tasks of central banks and policymakers in making policy decisions...It also raises the likelihood of policy mistakes if political interference leads to compromise in data quality, reliability, and timeliness.
*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.
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 