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Environmental evaluations of a “hard hat” residential area in rural Australia
Author(s) -
Murdoch Vincent J.,
Snyder Conrad W.,
Law Henry G.,
Pamment Peter R.,
Payne Patricia V.
Publication year - 1985
Publication title -
journal of community psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.585
H-Index - 86
eISSN - 1520-6629
pISSN - 0090-4392
DOI - 10.1002/1520-6629(198510)13:4<360::aid-jcop2290130405>3.0.co;2-2
Subject(s) - happiness , environmental quality , geography , resource (disambiguation) , government (linguistics) , locality , population , socioeconomics , psychology , variance (accounting) , social psychology , business , demography , sociology , ecology , computer science , computer network , linguistics , philosophy , accounting , biology
As the resource‐rich Australian continent is developed, increasing numbers of temporary townships are established or grafted onto small, dormant population centers to house the work force. This study investigates environmental evaluations in one such rural town. Construction workers and wives living in Nanango, a remote community serving the Tarong Power Station construction site in southeast Queensland, provided survey self‐report ratings of (a) the availability of environmental features, (b) their importance to overall life quality, and (c) the extent to which they bring happiness and satisfaction. Tucker's three‐mode common factor analysis method was used to explicate the individual differences in environmental evaluations among these residents. Nanango is portrayed in terms of independent feature domains associated with locality, natural/physical environs, company‐provided services, home, and government‐felt‐influence. Across the range of environmental features, valence evaluations, reflecting the communality of happiness and satisfaction reactions, seem to originate from a different criterial base than do importance judgments. Tucker's three‐mode factor analysis method appears to be a useful way of partitioning individual differences variance in environmental evaluations.