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Two reasons to make aggregated probability forecasts more extreme

Baron, Jonathan; Mellers, Barbara A.; Tetlock, Philip E.; … - In: Decision analysis : a journal of the Institute for … 11 (2014) 2, pp. 133-145

Persistent link: https://www.econbiz.de/10010382759

Hidden experts in the crowd : using meta-predictions to leverage expertise in single-question prediction problems

Wilkening, Tom; Martinie, Marcellin; Howe, Piers D. L. - In: Management science : journal of the Institute for … 68 (2022) 1, pp. 487-508

Persistent link: https://www.econbiz.de/10012821209

The contingent wisdom of dyads : when discussion enhances vs. undermines the accuracy of collaborative judgments

Minson, Julia A.; Mueller, Jennifer S.; Larrick, Richard P. - In: Management science : journal of the Institute for … 64 (2018) 9, pp. 4177-4192

Persistent link: https://www.econbiz.de/10011921508

Extracting the wisdom of crowds when information is shared

Palley, Asa B.; Soll, Jack B. - In: Management science : journal of the Institute for … 65 (2019) 5, pp. 2291-2309

Persistent link: https://www.econbiz.de/10012039760

Boosting the wisdom of crowds within a single judgment problem : weighted averaging based on peer predictions

Palley, Asa B.; Satopää, Ville A. - In: Management science : journal of the Institute for … 69 (2023) 9, pp. 5128-5146

Persistent link: https://www.econbiz.de/10014392893

Forecasting elections with mere recognition from small, lousy samples: A comparison of collective recognition, wisdom of crowds, and representative polls

Gaissmaier, Wolfgang; Marewski, Julian N. - In: Judgment and Decision Making 6 (2011) 1, pp. 73-88

We investigated the extent to which the human capacity for recognition helps to forecast political elections: We compared naive recognition-based election forecasts computed from convenience samples of citizens' recognition of party names to (i) standard polling forecasts computed from...

Persistent link: https://www.econbiz.de/10008835323