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Community engagement and subgroup meta-knowledge: some factors in the soul of a community

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  • Amelia A. McNamara

    (University of California, Los Angeles)

Abstract

The Knight Foundation collects data to determine what factors impact community satisfaction, local GDP growth, and interest in Knight news publications. For the 2013 Data Expo at the Joint Statistical Meetings, participants created graphical explorations of these data. This article focuses on the idea of community meta-knowledge, which is essentially majority group empathy or understanding of how minorities experience their community. For example, the survey asks participants to rate their community “as a place for senior citizens,” on a 5-point Likert scale. A city where seniors rated their community in the same way as non-seniors is defined as a community with high meta-knowledge about conditions for seniors. Three minority groups were explored: seniors, families with young children, and racial minorities. In most communities, people outside the minority group tended to under-rate their community, compared to those in the minority group. However, meta knowledge about racial minorities stood out as an exception.

Suggested Citation

  • Amelia A. McNamara, 2019. "Community engagement and subgroup meta-knowledge: some factors in the soul of a community," Computational Statistics, Springer, vol. 34(4), pages 1511-1535, December.
    • Handle: RePEc:spr:compst:v:34:y:2019:i:4:d:10.1007_s00180-019-00879-x
    DOI: 10.1007/s00180-019-00879-x
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    References listed on IDEAS

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    1. Heike Hofmann & Hadley Wickham & Dianne Cook, 2019. "The 2013 Data Expo of the American Statistical Association," Computational Statistics, Springer, vol. 34(4), pages 1443-1447, December.
    2. Heiberger, Richard & Robbins, Naomi, 2014. "Design of Diverging Stacked Bar Charts for Likert Scales and Other Applications," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 57(i05).
    3. Wickham, Hadley, 2011. "The Split-Apply-Combine Strategy for Data Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i01).
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    Cited by:

    1. Heike Hofmann & Hadley Wickham & Dianne Cook, 2019. "The 2013 Data Expo of the American Statistical Association," Computational Statistics, Springer, vol. 34(4), pages 1443-1447, December.

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