One of the challenges in identifying and correcting bias in data collection and analysis is that the methodologies used can sometimes be opaque. By promoting transparency in how data is collected, processed, and analyzed, we can uncover hidden biases that might skew results. Making methodologies public and subject to scrutiny allows for a more collaborative approach to identifying and addressing biases, ensuring the reliability and inclusivity of the data.
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