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The Alternative Factors Leading to Replication Crisis: Prediction and Evaluation
1Department for Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.
Abstract:
Most existing solutions to the current replication crisis in science address only the factors stemming from specific poor research practices. We introduce a novel mechanism that leverages the experts' predictive abilities to analyze the root causes of replication failures. It is backed by the principle that the most accurate predictor is the most qualified expert. This mechanism can be seamlessly integrated into the existing replication prediction market framework with minimal implementation costs. It relies on an objective rather than subjective process and unstructured expert opinions to effectively identify various influences contributing to the replication crisis.
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