Financial Times Article Rating

Young people are paying for social care with little in return

Sep 13, 2021 View Original Article
  • Bias Rating

    20% Somewhat Conservative

  • Reliability

    N/AN/A

  • Policy Leaning

    20% Somewhat Conservative

  • Politician Portrayal

    -4% 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

N/A

  •   Liberal
  •   Conservative
SentenceSentimentBias
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Bias Meter

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-100%
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100%
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Bias Meter

Contributing sentiments towards policy:

57% : Thus including social care in the Beveridge framework of social insurance is the right policy direction.
55% : On a wider canvas, it is not only what younger people pay in tax that matters but also what society offers them, notably helping to build their skills.
53% : As a result, insurers cannot price policies accurately so private insurance for social care is expensive, if offered at all.
53% : As part of intergenerational fairness, the government's current consideration of that review should consider rebalancing the relative contribution of tuition fees and taxpayer support for teaching, thus reducing the size of student loans.
51% : The government is right to treat the finance of social care as an insurance issue, but should take a wider view of fairness across generations.
42% : Private insurance deals with many risks.
40% : However, the risk that a person may need social care many decades in the future faces huge uncertainties, both about the risk and the cost of care.
39% : Though sounding radical, that is the arrangement in Germany, where pensioners continue to pay the premium for social care since that is a risk they continue to face.
37% : Needing social care at some stage in the future is precisely such a risk.

*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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