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Related Questions
- How can human evaluators be recruited to ensure diversity and representation of the population being evaluated?
- What are the potential biases that human evaluators may introduce, and how can they be mitigated?
- What strategies can be employed to ensure that human evaluators are representative of the population being evaluated, such as demographic matching or training?
- How can human evaluators be incentivized to provide accurate and unbiased evaluations?
- What are the consequences of having a non-representative group of human evaluators on the validity and generalizability of the evaluation results?
- Can machine learning algorithms be used to identify and mitigate biases in human evaluator ratings?
- What role do contextual factors, such as cultural background and education level, play in shaping human evaluator biases, and how can they be accounted for in evaluation design?
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