The development of methodologies for the analysis of stakeholder feedback can bring consistency and robustness to public participation processes. Communities invest time, energy, and wisdom in civic engagement efforts; their contributions should be ethically examined and communicated to advance equity goals and ensure collective effectiveness.
Following a research-based approach, we first identify problems or issues through the lens of our collaborators and analyze the context in which they unfold. This first step is essential to the development of an independent interpretation and supports the articulation of clear research questions. These questions provide overall structure and inform the selection of data collection methods. These early decisions are documented in the methodology to ensure transparency, and they are further refined through the course of the project. Once data is collected and organized, the methodology will guide collaborative analysis efforts. Coding, a key process in qualitative analysis, entails reading transcripts and other textual inputs to identify distinct themes. In other words: Searching for patterns in the data and assigning tags. This process provides structure to thematic analysis, and allows core themes and contextual relationships to emerge.
As new data becomes available, it is integrated into the analysis. The triangulation of qualitative data (context) with abstract, quantitative data (content), can lead to new insights and enhance the credibility of findings. Integrated data analysis, also known as mixed methods, provides a more comprehensive picture of the issues being explored. The use of demographic data in our research is a good example of this integration: the overlay of quantitative data (who) and qualitative data (what) often generates deeper insights and supports relative and aggregate analysis of the data.
The use of computer software to facilitate mixed methods analysis is a notable development. Our team uses NVivo to aggregate, organize, analyze, and visualize data more effectively, to conduct deeper analysis, and validate findings. Features such as auto-coding, queries, and sentiment analysis, support manual (researcher-led) analysis.
For collaborators and participants, a methodology provides certainty on how data and private information will be managed, used, stored, and protected throughout the life of the project and beyond. To public participation processes, a rigorous methodology brings greater transparency and enhances our collaborators’ accountability to participants and their contributions.