Data Methodology

The first five years of the CRC research program explored the dynamic relationship between the meaning of place, limits, scale and diversity. The CRC renewal (September 2009 to 2014) is exploring the relationship, if any, between three heuristics—anticipatory governance, resilience and innovation. The research program was equally interested in communities of place and virtual communities. The basic research methodology we selected was the development of multiple case studies which is described in that section of the website and on-line real-time synchronous e-Dialogues.

The Principal Investigator, Professor Ann Dale, has now led over 50 e-Dialogues, and the on-line case study library contains over 50 Canadian case studies. People criticize case study research as not being generalizable to other organizations, or communities, the unit under study as well as biases of information, and misjudging the representativeness of a single event (Tversky and Kahneman, 1986), exaggerating the salience of the information because of its ready availability. We feel that issues of generalizability and reliability are more than overcome by using a meta-case analysis, based on the ‘thick’ data contained in the case study library.

In addition to case study methodology, we triangulated our data through the following steps. Our first step was to develop an overall thematic coding framework. Thematic coding is used to identify commonalities, differences and patterns (Seidel and Kelle, 1995) emerging from the case studies. The research team developed the initial framework iteratively, going back and forth between data-driven coding (grounded theory) and concept driven coding (Gibbs, 2007). The concept driven coding was place, anticipatory governance, resilience and innovation. The framework was then cross-validated with the codes that had been generated from another project derived from a 50 journal article database on the most seminal journal articles on sustainable development. The revised coding framework was then thrown back and forth and finalized with an expanded trans-disciplinary team of researchers and community practitioners.

The data was analyzed using computer-assisted qualitative data analysis software (CAQDAS) in order to empirically derive insights on conceptual relationships. The software used was NVivo, selected for its ability to code large data sets, illuminate areas of coding convergence and compare similarities in coding and types of terms found in a data set.


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Gibbs, C. G. R. 2007. Analyzing qualitative data, 38–56. doi:10.4135/9781849208574

Seidel, J., & Kelle, U. (1995). Different functions of coding in the analysis of textual data. Computer-aided qualitative data analysis: Theory, methods, and practice, 52-61.

Tversky, A. and D. Kahneman. 1986. Rational choice and the framing of decisions. The Journal of Business, October, 251-278