5 research outputs found

    Leveraging U.S. Army Administrative Data for Individual and Team Performance

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    The Army possesses vast amounts of administrative (archival) data about Soldiers. These data sources include screening tests, personnel action codes, training scores, global assessments, physical fitness scores, and more. However, the Army has yet to integrate these data to create a holistic operating picture. Our research focuses on repurposing Army administrative data to (1) operationalize social constructs of interest to the Army (e.g., Army Values, Warrior Ethos) and (2) model the predictive relationship between these constructs and individual (i.e., Soldier) and team (i.e., unit) performance and readiness. The goal of the project is to provide people analytics models to Army leadership for the purposes of optimizing human capital management decisions. Our talk will describe the theoretical underpinnings of our human performance model, drawing on disciplines such as social and industrial/organizational psychology, as well as our experience gaining access to and working with Army administrative data sources. Access to the archival administrative data is provided through the Army Analytics Group (AAG), Person-event Data Environment (PDE). The PDE is a business intelligence platform that has two central functions: (1) to provide a secure repository for data sources on U.S. military personnel; and (2) to provide a secure collaborative work environment where researchers can access unclassified but sensitive military data

    Leveraging U.S. Army Administrative Data for Individual and Team Performance

    Get PDF
    The Army possesses vast amounts of administrative (archival) data about Soldiers. These data sources include screening tests, personnel action codes, training scores, global assessments,  physical fitness scores, and more. However, the Army has yet to integrate these data to create a holistic operating picture. Our research focuses on repurposing Army administrative data to (1) operationalize social constructs of interest to the Army (e.g., Army Values, Warrior Ethos) and (2) model the predictive relationship between these constructs and individual (i.e., Soldier) and team (i.e., unit) performance and readiness. The goal of the project is to provide people analytics models to Army leadership for the purposes of optimizing human capital management decisions. Our talk will describe the theoretical underpinnings of our human performance model, drawing on disciplines such as social and industrial/organizational psychology, as well as our experience gaining access to and working with Army administrative data sources. Access to the archival administrative data is provided through the Army Analytics Group (AAG), Person-event Data Environment (PDE). The PDE is a business intelligence platform that has two central functions: (1) to provide a secure repository for data sources on U.S. military personnel; and (2) to provide a secure collaborative work environment where researchers can access unclassified but sensitive military data

    Seeing Wrath from the Top (through Stratified Lenses): Perceivers High in Social Dominance Orientation Show Superior Anger Identification for High-Status Individuals

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    In this research, we test the hypothesis that social status will be an orienting cue to the identification of facial expressions of emotion, particularly angry expressions, especially for those who dispositionally believe that some societal groups should dominate others (Social dominance orientation; Pratto, Sidanius, Stallworth, & Malle, 1994). Using an emotion identification task, the expression of anger was identified with greater accuracy on high-status faces than low-status faces, but only for people who endorsed rigid social hierarchies (i.e., high SDO). Furthermore, people who did not endorse social hierarchies (i.e., low SDO) did not show a preference for high-status anger. Thus, the current findings provide a novel account of how social status can be an informative cue to the expression of anger in online perceptions, especially for those who view social dominance as an important framework for society

    Response Times in Economics: Looking Through the Lens of Sequential Sampling Models

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