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Getting the Big Picture in Community Science: Methods That Capture Context
Author(s) -
Luke Douglas A.
Publication year - 2005
Publication title -
american journal of community psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.113
H-Index - 112
eISSN - 1573-2770
pISSN - 0091-0562
DOI - 10.1007/s10464-005-3397-z
Subject(s) - consilience , data science , context (archaeology) , community psychology , health psychology , argument (complex analysis) , sociology , computer science , management science , social science , epistemology , psychology , social psychology , public health , geography , engineering , medicine , philosophy , biochemistry , chemistry , nursing , archaeology
Community science has a rich tradition of using theories and research designs that are consistent with its core value of contextualism. However, a survey of empirical articles published in the American Journal of Community Psychology shows that community scientists utilize a narrow range of statistical tools that are not well suited to assess contextual data. Multilevel modeling, geographic information systems (GIS), social network analysis, and cluster analysis are recommended as useful tools to address contextual questions in community science. An argument for increased methodological consilience is presented, where community scientists are encouraged to adopt statistical methodology that is capable of modeling a greater proportion of the data than is typical with traditional methods.