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Geography Matters: Discerning the Importance of Local Context

Published online by Cambridge University Press:  27 January 2017

Beth Mitchneck
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Abstract

Basic geographical considerations like distance and resource location do influence political and economic processes; yet, focusing on additional geographical concepts such as relative location, relational space, and embedded sociospatial relationships strengthens and deepens analysis to reveal easily overlooked factors and implications of transition. Beth Mitchneck uses the example of survey research on Russia's transition, now prevalent in study of the region, to show that identifying spatial and regional variation is not always a simple or straightforward process and that incorporating nuanced geographical concepts into both the construction and analysis of a survey instrument about local politics reveals regions as settings for social practice. By shifting from a paradigm where regions are containers in physical space to one where regions are settings in which social behavior and action is situated, she suggests that inconsistent experience of transition processes are related to regional or spatial variation.

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Articles
Information
Slavic Review , Volume 64 , Issue 3 , Fall 2005 , pp. 491 - 516
Copyright
Copyright © Association for Slavic, East European, and Eurasian Studies. 2004

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References

The author gratefully acknowledges funding support from the National Science Foundation, the National Council for Eurasian and East European Research, and the University of Arizona. The Russian collaborator Alexander Gasparishvili deserves great credit for conceptualization of the project as well as making sure it happened. The author also thanks Nir Cohen and James Bell as well as anonymous reviewers for helpful comments. All the usual disclaimers apply.

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15 Mitchneck,“Regional Governance Context in Russia.”

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20 See Putnam, Robert D., Making Democracy Work: Civic Traditions in Modern Italy (Princeton, 1993)Google Scholar, for a seminal work on social capital, and Stoner-Weiss, Local Heroes, for an example of related research on Russia.

21 Frye,“Capture or Exchange?”

22 James E. Bell, A Place for Community ? Urban Social Movements and the Struggle over the Space of the Public in Moscow (Ph.D. diss., University of Washington, 1997).

23 Pickvance, Chris G.,“Housing Privatization and Housing Protest in the Transition from State Socialism: A Comparative Study of Budapest and Moscow,” International Journal of Urban and Regional Research 18 (1994): 433–50;CrossRefGoogle Scholar Shomina, E.,“Stanovlenie zhilishchnogo dvizheniia v Rossii,” Sotsiologicheskie issledovaniia 22, no. 10 (1995): 78–87.Google Scholar

24 Baldersheim et al., Local Democracy and the Processes of Transformation in East-Central Europe.

25 Economist Intelligence Unit, Country Profile, Russia, 2000 (London, 2000).

26 Ibid.

27 In addition to summary analyses of the survey responses, I employed a standard analytical technique to classify the responses by regions into like groups: cluster analysis. Cluster analysis would group regions by similar responses signifying regional or spatial groups. The cluster analysis resulted in the summation of the data into one cluster and in some cases into two clusters where the second cluster had only a handful of regions in the cluster. These findings suggest that this standard technique to describe regions is not analytically useful in this case.

28 Open-ended questions allow the respondent to identify the important topics rather than choose among those identified by the researcher. This technique is especially useful when the goal of the question is to seek an opinion without constraining the respondent to preconceived responses. The open-ended question reduces the probability of analytical error by allowing the respondent to raise a variety of options that the researcher may not have considered.

29 Spearman's rho suggests a strong association between the executive and representative branches (0.768) and a significant yet weaker association between urban and regional officials (0.439). I used other techniques, like cluster analysis, to group responses by region. All analyses of this sort were unsuccessful and resulted in the identification of only one cluster, supporting the general lack of regional variation.

30 Semiclosed questions include the option of identifying“other” responses not specified by the researcher.

31 Pearson r's, comparing mean responses for demographic and economic factors, are 0.986 for executive versus representative and 0.996 for urban versus regional. Paired t-tests for the hypothesis that the responses are identical across these groups confirms the strong association in that not one t statistic allowed for rejection of the hypothesis. The t statistics are 0.58 for branch and 0.28 for urban versus regional.

32 Pearson r's are 0.974 for executive versus representative and 0.664 for urban versus regional.

33 Pearson r's also are very strong for the influence of participants: 0.983 for executive versus representative and 0.970 for urban versus regional.

34 Frye,“Capture or Exchange?"

35 Clarke, Susan and Gaile, Gary, The Work of Cities (Minneapolis, 1998).Google Scholar

36 Using the dependent variable example of the importance of age structure for identifying policy priorities, the two types of equations follow. The linear trend surface equation is:

The quadratic trend surface equation is:

As with standard regression analysis, I use an F test to evaluate the validity of the model results and t-tests to assess the statistical significance of the regression coefficients.

37 The linear equations had the following results for the question regarding the three most important policy problems. The * indicates that the Model R2 was not statisti-cally significant.

38 Lynn,“Geography and Transition.”

39 The results of the quadratic equations from the trend surface analysis were:

40 The results of the linear equations from the trend surface analysis were:

41 Clarke, Susan and Gaile, Gary,“Moving toward Entrepreneurial Economic Development Policies: Opportunities and Barriers,” Policy Studies Journal 17, no. 2 (Summer 1989): 574–98.CrossRefGoogle Scholar

42 The results of the quadratic trend surface analysis equations were:

43 See King, Leslie J., Statistical Analysis in Geography (Englewood Cliffs, N.J., 1969)Google Scholar, for nearest neighbor analysis. See Ragin, Charles C., Fuzzy-Set Social Science (Chicago, 2000)Google Scholar, and Hoppner, Frank, Klawonn, Frank, Kruse, Rudolf, and Runkler, Thomas, Fuzzy Cluster Analysis: Methods for Classification, Data Analysis, and Image Recognition (Chichester, Eng., 1999)Google Scholar, for fuzzy set analysis. And see Derudder, B. and Witlox, F.,“Classification Techniques in Complex Spatial Databases: On the Assessment of a Network of World Cities,” Solstice: An Electronic Journal of Geography and Mathematics 13, no. 1 (Summer 2002): 1–32 Google Scholar (http://www-personal.umich.edu/∼sarhaus/image/solstice/sum02/derudder.pdf, last consulted 8 April 2005), for a good review of various classification techniques.