Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 60,240 bioRxiv papers from 267,843 authors.
Forecasting is an increasingly important part of our daily lives. Many studies on how people produce forecasts frame their behavior as prone to systematic errors. Based on recent evidence on how people learn about functions, we propose that participants' forecasts are not irrational but rather driven by structured priors, i.e. situationally induced expectations of structure derived from experience with the real world. To test this, we extract participants' priors over various contexts using a free-form forecasting paradigm. Instead of exhibiting systematic biases, our results show that participants' priors match well with structure found in real-world data. Moreover, given the same data set, structured priors induce predictably different posterior forecasts depending on the evoked situational context.
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