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SFGate Article Rating

Why getting the numbers right isn't enough for pollsters to be credible in today's polarized climate

Mar 07, 2025 View Original Article
  • Bias Rating

    10% Center

  • Reliability

    85% ReliableGood

  • Policy Leaning

    10% Center

  • Politician Portrayal

    -8% Negative

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

6% Positive

  •   Liberal
  •   Conservative
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Bias Meter

Contributing sentiments towards policy:

56% : Yet, despite statistical accuracy, public perception tells a different story.
54% : Forecasters like Nate Silver have shaped public expectations about such metrics.
53% : While the 2024 polls performed within historical norms, public expectations have raised the bar for what qualifies as accurate polling.
52% : The final result - Trump 49.8%, Harris 48.2% - fell within the expected range of outcomes.
51% : Polling must be framed within the broader context of political and social change, making sense of uncertainty rather than just quantifying future likelihoods.
49% : Trump successfully positioned himself as the champion of this discontent.
48% : Consider Silver's 2024 forecast, which gave Harris and Trump each a 50% chance of winning.
28% : Yes, pollsters underestimated Trump in 2016, 2020 and again in 2024.
26% : The political right claimed polls systematically underestimated Trump, while the left accused pollsters of falsely portraying the 2024 race as close.
10% : Other indicators consistently suggested Trump had the upper hand, such as weak Biden approval ratings, belief that the country was on the wrong track, and the strength of candidates on the main issue, inflation.

*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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