Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Jason L. Harman"'
Publikováno v:
Discover Psychology, Vol 3, Iss 1, Pp 1-11 (2023)
Abstract Digital maps are important for many decision-making tasks that require situational awareness, navigation, or location-specific data. Often, digital mapping tools must generate a map that displays labels near associated features in a visually
Externí odkaz:
https://doaj.org/article/8dfb5868e83e40efad601daf1757ea86
Publikováno v:
Discover Psychology, Vol 3, Iss 1, Pp 1-5 (2023)
Abstract Objectives Digital map applications produce maps on the fly, using label placement algorithms to optimize the map layout for various factors. Previous work has made great strides in quickly generating layout placement algorithms that minimiz
Externí odkaz:
https://doaj.org/article/6d3280abbd2e4df29595ecda05fd2bc3
Autor:
Jason L. Harman, Jaelle Scheuerman
Publikováno v:
Discover Artificial Intelligence, Vol 3, Iss 1, Pp 1-5 (2023)
Abstract Machine learning (ML) algorithms are often assumed to be the most accurate way of producing predictive models despite problems with explainability and adverse impact. The 3rd annual Society for Industrial and Organizational Psychology Machin
Externí odkaz:
https://doaj.org/article/f6ddf442e92a497da757b73697fd0a6c
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
Abstract Effective risk communication during the COVID-19 pandemic is critical for encouraging appropriate public health behaviors. One way that the public is informed about COVID-19 numbers is through reports of daily new cases. However, presenting
Externí odkaz:
https://doaj.org/article/162c37565c864d5bb418849a930adc93
Publikováno v:
Frontiers in Psychology, Vol 10 (2019)
In this paper, we review basic findings from experimental studies in judgment and decision making that could contribute to designing policies and trainings to enhance police decision making. Traditional judgment and decision-making research has focus
Externí odkaz:
https://doaj.org/article/41abcc4cb6ba41e7a6b86d72989231a3
Autor:
Jason L. Harman, Kayla D. Brown
Publikováno v:
International Journal of Selection and Assessment. 30:157-166
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::da4b73aef268674d97e03bac92cb5f2e
https://doi.org/10.1111/ijsa.12374
https://doi.org/10.1111/ijsa.12374
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
Scientific Reports
Scientific Reports
Effective risk communication during the COVID-19 pandemic is critical for encouraging appropriate public health behaviors. One way that the public is informed about COVID-19 numbers is through reports of daily new cases. However, presenting daily cas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::61eafab9d51eb4e03b05d1a3ca823d80
https://doaj.org/article/162c37565c864d5bb418849a930adc93
https://doaj.org/article/162c37565c864d5bb418849a930adc93
Autor:
Jason L. Harman, Jaelle Scheuerman
The 3rd annual SIOP Machine Learning (ML) Competition sought to find ML models for personnel selection that could balance the best of ML prediction balanced with the constraint of not increasing adverse impact. To test the possible advantages of simp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1e9e67e0fa9ed7f816ce32b3293fcf54
https://doi.org/10.31234/osf.io/8vpdx
https://doi.org/10.31234/osf.io/8vpdx
Autor:
Jason L. Harman, Justin Purl
Publikováno v:
Trends in Psychology.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::256d3c760b7cf84034c526e886d29579
https://doi.org/10.1007/s43076-022-00162-x
https://doi.org/10.1007/s43076-022-00162-x
Publikováno v:
Current Psychology. 41:5795-5802
The interaction between goals and affect in decision making is not well understood. We test the affective-motivational route theory (AMR: Aarts et al. 2008b) which predicts that positive affect primed along with a goal leads to goal pursuit, whereas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0b45fbf441e8a0b828dd236bc7731237
https://doi.org/10.1007/s12144-020-01048-w
https://doi.org/10.1007/s12144-020-01048-w