Bonded to whom? Social interactions in a high-amenity rural setting

Abstract

Beginning with Kasarda and Janowitz, several dimensions of community attachment have been theorized. The local social bonds or the interpersonal dimension of community attachment is reflected in social interaction with family, friends and neighbors. A current trend within the United States is the influx of seasonal residents into high-amenity areas. Whether this influx affects the types ofsocial bonds formed in such areas is an important and unanswered question. This study attempts to determine whether second homeowners in selected high-amenity areas in rural Utah are interacting socially within their seasonal communities, and whether those social interactions extend across residential categories. Results indicate seasonal residents who most frequently visit their secondary communities interact socially with their friends and neighbors at similar or higher levels to year-round residents. Also, a mixed neighborhood composition plays an important role in the social interactions that transcend residential categories.

Keywords:

• rural community development
• natural resources
• migration

Acknowledgements

The authors would like to acknowledge and thank Donald R. Field and A.E. Luloff for their participation in the larger research project from which data for this paper was drawn. This project was conducted with major funding support from the National Research Initiative Competitive Grants Program administered by the U.S. Department of Agriculture Cooperative Research Service, Grant #USDA CSREES 2003-35401-12889.

 Significant additional funding was provided by the Utah Agricultural Experiment Station, Project # UAES 00839.

Notes

1. The specific question asked: “How often do you interact socially with your friends, relatives and neighbors in activities such as having dinner, sitting and talking, recreating, or going out together? Please check the appropriate response for friends, relatives, and neighbors.” Respondents were given the following choices for each of the three indicators: (1) daily; (2) several times a week; (3) about once a week; (4) several times a month; (5)about once a month; (6) several times a year; and (7) rarely or never. These responses were recoded so a higher score indicated greater social interaction.

2. Each of the five indicators were scored on a Likert scale with values ranging from one (strongly agree) to five (strongly disagree). Each was rescaled so higher scores were equivalent to higher levels of attachment. The summated index produced values ranging from five to 25. Chronbach's alpha for the index was 0.89, with inter-item correlations ranging from 0.52 to 0.69.

3. The measure used to create this categorization is a question asking respondents to “Please estimate the number of days each season you spend at your seasonal or vacation home in Utah in a typical year.” The numbers provided for each season were then summed to create the measure estimating yearly visitation days for each respondent.

4. Income was measured by asking “Which of the following categories best describes your pre-tax annual household income for 2003?” The response categories for this question included: (1) less than $15,000; (2) $15,000 to $24,999; (3) $25,000 to $34,999; (4) $35,000 to $49,999; (5) $50,000 to $74,999; (6) $75,000 to $99,999; (7) $100,000 to $149,999; and (8) $150,000 or more.

5. A respondent's education was measured by asking “What is the highest level of education that you have completed (please mark one category)?” Response categories included: (1)less than a high school degree; (2) high school degree or GED; (3) Associate Degree or some college; (4) four-year college degree (BA/BS); and (5) advanced degree (master's, PhD, JD, MD).

6. These stages were: (1) the young individual or couple with no children (age less than 40); (2) the individual or family with young children (under the age of five only); (3) individuals or families with a mix of young children and older children (age six to 18); (4) individuals or families with older children only; (5) middle-aged adults with no children (age 40–64); and (6) individuals or couples who are in the retirement portions of their lives (age 65 orolder) and either do not have children or have children who are adults themselves (over18).

7. Respondents were asked: “What is your religious affiliation, if any?” and given the option of choosing either protestant, catholic, LDS, none or other; for analytic purposes, respondents were dichotomized – those who were members of the LDS faith and those who were not. Political orientation was measured via the question: “Which of the following best describes your political views?” The answer choices consisted of (1) conservative, (2) moderate conservative, (3) moderate, (4) moderate liberal, (5) liberal and (6) other. For analytical purposes, however, the few respondents who reported their political orientation as “other” were dropped in order to maintain the ordinal nature of responses across the political spectrum.

8. It was determined using the statistical software HLM 6 (hierarchical linear modeling) that very little variation in the dependent variables was explained by county of residence. Theintraclass correlations, which provide a measure of the amount of variation explained by a respondent's county, were all less than 1%.