queries.json

{
  "governance_questions": "Does data governance enable or disable oppression? Does it address structural inequality? Are data practices aligned with community goals? Is there equitable access to benefits? Are affected populations involved in decision-making?",
  "discrimination_focus": "Data-driven discrimination against poor, marginalized and vulnerable populations. Biometric databases excluding those with worn fingerprints. Surveillance of migrants and refugees. Algorithmic systems that disadvantage based on socio-economic status.",
  "core_concept": "Data Justice means fairness in how data practices distribute benefits and harms. It involves equitable access, discrimination prevention, and inclusive governance.",
  "3_pillars": "Three pillars of data justice: 1. Visibility - right to representation and privacy 2. Engagement - right to benefit from data and retain autonomy 3. Non-discrimination - right to be free from discrimination and claim redress",
  "health_equity": "Equitable access to healthcare through digitalisation. Patient sovereignty and informed consent. Stakeholder participation in health data governance. Rural access to telemedicine and digital health services.",
  "Algorithmic bias": "How is algorithmic bias discussed in the context of healthcare?"
}