Ghana adds 330,000 jobs yet youth unemployment crisis deepens alarmingly
- Bias Rating
- Reliability
N/AN/A
- Policy Leaning
-74% Very Left
- Politician Portrayal
N/A
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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
-15% Negative
- Liberal
| Sentence | Sentiment | Bias |
|---|---|---|
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
Extremely
Liberal
Very
Liberal
Moderately
Liberal
Somewhat Liberal
Center
Somewhat Conservative
Moderately
Conservative
Very
Conservative
Extremely
Conservative
-100%
Liberal
100%
Conservative
Contributing sentiments towards policy:
64% : Possible explanations include skills mismatches where youth lack competencies employers seek, credential inflation requiring excessive qualifications for entry positions, inadequate information connecting jobseekers to vacancies, and discrimination based on networks or backgrounds rather than merit.62% : Job quality, productivity, and economic security matter equally for household welfare and development outcomes.
61% : Expanding quality service employment requires investments in education, technology infrastructure, and regulatory frameworks enabling modern service industries including finance, information technology, professional services, and tourism.
58% : Rather than forcing formalization imposing unsustainable costs, policies might focus on improving informal sector productivity through access to credit, training, market linkages, and gradual integration into regulatory frameworks offering benefits alongside obligations.
50% : Limited government fiscal capacity restricts public employment expansion and subsidy programs.
*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.