Item request has been placed! ×
Item request cannot be made. ×
loading  Processing Request

Seeing Like a Geologist: Bayesian Use of Expert Categories in Location Memory

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
اقرأ على الانترنت اقرأ أكثر حفظ في قائمتي
  • معلومة اضافية
    • Peer Reviewed:
      Y
    • المصدر:
      15
    • Sponsoring Agency:
      National Science Foundation (NSF)
    • Contract Number:
      SBE0541957
      SBE1041707
    • الموضوع:
      Memory; Spatial Ability; Bias; Bayesian Statistics; Expertise; Geology; Error Patterns; Information Sources; Organic Chemistry; English Literature; Classification; Models; Novices
    • الرقم المعرف:
      10.1111/cogs.12229
    • ISSN:
      0364-0213
    • نبذة مختصرة :
      Memory for spatial location is typically biased, with errors trending toward the center of a surrounding region. According to the category adjustment model (CAM), this bias reflects the optimal, Bayesian combination of fine-grained and categorical representations of a location. However, there is disagreement about whether categories are malleable. For instance, can categories be redefined based on expert-level conceptual knowledge? Furthermore, if expert knowledge is used, does it dominate other information sources, or is it used adaptively so as to minimize overall error, as predicted by a Bayesian framework? We address these questions using images of geological interest. The participants were experts in structural geology, organic chemistry, or English literature. Our data indicate that expertise-based categories influence estimates of location memory--particularly when these categories better constrain errors than alternative ("novice") categories. Results are discussed with respect to the CAM.
    • نبذة مختصرة :
      As Provided
    • الموضوع:
      2016
    • الرقم المعرف:
      EJ1094304