From teen mom to triumph: A story of perseverance and success
- Bias Rating
78% Very Conservative
- Reliability
30% ReliableFair
- Policy Leaning
-10% Center
- Politician Portrayal
N/A
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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
14% 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%
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Contributing sentiments towards policy:
68% : The road to becoming a medical doctor while balancing the responsibilities of parenthood demanded short-term sacrifices that weighed heavily on my heart.65% : Despite the ache of separation, I was driven by the vision of long-term benefits - the opportunity to provide my child with a stable and fulfilling life, filled with opportunities that I could only dream of.
58% : The weight of responsibility pressed heavily on my shoulders, and the judgment of others only exacerbated my sense of isolation.
58% : It was nurtured by the support of my family and the unwavering love of my child who believed in me when I struggled to believe in myself.
57% : But amid uncertainty and fear, I made a choice - a choice to use this adversity into the fuel to ignite my determination.
55% : However, I held onto the belief that these sacrifices were essential for securing a brighter future not just for myself, but for my child as well.
50% : 'WE'RE FAMILY'But each time I stumbled, I reminded myself of the promise I made to my child and to myself - to create a better future, no matter the obstacles.
40% : Spending less time with my child in those formative years was a painful trade-off, one that often filled me with guilt and longing.
*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.