Good Judgment (Forecasting) - Footnote 80
The claim that judgmental forecasting approaches are fundamentally constrained by forecasters' inherent biases is not directly supported by the source. The source mentions that experts are often overconfident, but this is in the context of aggregation algorithms, not judgmental forecasting approaches in general. The claim that the ability to engage in reflective thinking is partly innate is supported, but the claim that it is only partly developed through training is an overclaim. The source says, "It’s part nature and part nurture,” he said. The source does not explicitly state that bias training is used by Good Judgment, but it does say that Good Judgment offers resources to train forecasters.
Our claim
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Source evidence
1 src · 1 checkNoteThe claim that judgmental forecasting approaches are fundamentally constrained by forecasters' inherent biases is not directly supported by the source. The source mentions that experts are often overconfident, but this is in the context of aggregation algorithms, not judgmental forecasting approaches in general. The claim that the ability to engage in reflective thinking is partly innate is supported, but the claim that it is only partly developed through training is an overclaim. The source says, "It’s part nature and part nurture,” he said. The source does not explicitly state that bias training is used by Good Judgment, but it does say that Good Judgment offers resources to train forecasters.