A Study of Expert Judgment in a Natural Setting
{'Code': '04050100', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SES', 'LongName': 'Divn Of Social and Economic Sciences'}}
{'SignBlockName': 'Shelton White', 'PO_EMAI': 'swhite@nsf.gov', 'PO_PHON': '7032920000'}
This proposal focuses on how weather forecasters make use of imperfect          information in making predictions.  The investigators were seen to              provide an unusual and appropriate mix of skills needed to test several         important theoretical questions about how experts assess the quality of         information and important applied questions about how weather forecasts         could be made more reliable.  The project involves two experiments,             using expert weather forecasters as the primary subject group, that             will (a) compare the accuracy of forecasts made in limited vs. full             information conditions and (b) test the consistency and reliability of          information acquisition by examining how different forecasters make use         of the same limited information base.  The use of operating weather             forecasters is viewed as particularly appropriate because, despite the          fact that meterorologists often are viewed as the paragon of excellence         in real-world probability judgments, their decision making processes            and their ability to interpret and make inferences on the basis of              incomplete information has not been thoroughly studied.  The results            will be general interest as a study of how experts make use of                  incomplete information and how human-computer interactions should be            designed to provide assistance to decision makers facing complex                forecasting demands under conditions of limited information.
{'FirstName': 'Thomas', 'LastName': 'Stewart', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Thomas R Stewart', 'EmailAddress': 't.stewart@albany.edu', 'NSF_ID': '000209157', 'StartDate': '05/01/1989', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'SUNY at Albany', 'CityName': 'Albany', 'ZipCode': '122220100', 'PhoneNumber': '5184374974', 'StreetAddress': '1400 Washington Ave MSC 312', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '20', 'CONGRESS_DISTRICT_ORG': 'NY20', 'ORG_DUNS_NUM': '152652822', 'ORG_LGL_BUS_NAME': 'RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK, THE', 'ORG_PRNT_DUNS_NUM': '020657151'}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
[{'Code': '1321', 'Text': 'Decision, Risk & Mgmt Sci'}, {'Code': '1525', 'Text': 'Physical & Dynamic Meteorology'}]
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1988&All=true', 'xml': '8822319.xml'}