Kate Sherren

Landscapes - People - Global change

Tag: Q-methodology

New paper on dykeland futures

Graphical abstract for a new paper in Land Use Policy on dykeland futures in Nova Scotia.

Graphical abstract for a new paper in Land Use Policy on dykeland futures in Nova Scotia.

Pleased to have a new paper out in Land Use Policy with former MREM intern Logan Loik on how Nova Scotians perceive agricultural dykelands in the face of climate change. Bay of Fundy dykelands are Canada’s only UNESCO-listed agricultural landscapes because of their origins in the 1600s with French settlers.  These structures protect little active farmland today, but governance is still in the hands of the farming sector. They are more often used for recreation, or to protect residential, commercial or transportation infrastructure. Climate projections suggest considerable effort and expense will be required to raise all dykes to the levels necessary to withstand sea level rise and storm surges, but it may be that decommissioning some dykes and restoring coastal wetlands may be more resilient. We asked 183 Nova Scotians to sort statements about dykelands, wetlands and coastal governance. The dominant discourse from this Q-method study was supportive of maintaining dykelands for recreational, cultural and flood protection reasons; the next most prevalent was pragmatically supportive of wetland restoration for efficiency purposes. Results suggest challenges for the process of managed realignment, as well as climate adaptation in cultural landscapes more generally, but also some new analytical opportunities for large-n Q-method research.

New energy Q paper in Environmental Sociology

Our national energy project implemented Q-method interviews in Alberta, Ontario and New Brunswick, where participants sorted a concourse of statements about energy beliefs, preferences and tradeoffs. A new paper in Environmental Sociology, Identifying energy discourses in Canada with Q methodology: moving beyond the environment versus economy debates, led by University of Alberta colleague John Parkins, discusses the five emergent discourses and their implications for advancing complex energy debates. It will be interesting to see how these discourses align, or not, with the large n (p-set) national sorting survey of the same statements that was implemented online last year. The abstract follows:

Drawing inspiration from the literature on social imaginaries and cultural models, this study explores contending perspectives on energy and sustainability, moving beyond a simplistic understanding of support or opposition to specific energy developments. With a comparative study in three regions of Canada, we use Q methodology to identify five key discourses on energy issues: (1) climate change is a primary concern, (2) maintain the energy economy, (3) build on the resilience of nature and local energy systems, (4) markets and corporations will lead and (5) renewable energy sources are the path forward. We find several under-examined perspectives on energy and society – one discourse that attempts to balance growth in the energy economy with environmental concern and another discourse that promotes the resilience of natural and local energy systems. We also find a proclivity towards science, ingenuity and technological innovation as a strategy to resolve contemporary challenges in the energy sector. This study helps to elaborate energy policy conversations beyond the common environment versus economy tropes. The study also reveals opportunities to forge common ground and mutual understanding on complex debates.

Hard at work

Energy team at work in Folly Beach

Energy team at work in Folly Beach

Fun with freeware

What am I doing today? I’m re-interpreting Q-method output for my dykeland study because of a late discovery about how PQMethod identifies ‘defining sorts’. Q-method uses statement-sorting (or photo-sorting, viz Milcu et al. ) to understand the public discourses that exist around a given issue. I seem to be doing quite a lot of it of late with students and colleagues, but this is the first time that I’ve been the analyst. Near-ubiquitous freeware program PQMethod does an outstanding job of providing statistical output that is easily interpreted, but it is important to dig into the manuals to understand the steps it takes along the way. Once factor analysis identifies various discourse ‘types’ based on sorting on a forced-normal distribution, PQMethod helpfully identifies ‘factor-defining’ sorts, which you can use to characterize each one. These are the individuals who sorted similarly, driving that particular ‘archetype’. Using the demographics of these defining sorts to be reflective of a discourse is particularly useful when you have a lot of sorts, which is a new use of Q-method which is not entirely consistent with the rationale behind its design. PQMethod identifies as ‘defining’ those sorts where: (1) The factor explains at least half of the common variance, that is, the factor loading for that particular respondent on a particular factor must be at least half of the variance explained by all factors pulled out of the model for that respondent; and, (2) the loading must be significant at p < .05. However, it also includes in that mix those for which the correlation (the loading) is negative, that is, the complete opposite. Perhaps for a qualitative interpretation of the factors this would be irrelevant, but I designed my concourse of statements such that scores could be derived to summarize perspectives on a range of themes. As folks like me push the method and the software to places it was not intended to go, it behooves us to be careful that we fully understand the tools we are using.

Knee deep in quantitative surveys

I was reflecting last night about a recent transition that has occurred in my research. After ten years of predominantly qualitative research, albeit increasingly of a semi-quantitative bent (e.g. using theme counts to filter significance), I am currently leading five quantitative surveys. I just finished writing up last year’s Nuisance Nature survey in New Brunswick and Nova Scotia, and am in the middle of writing up the online Q-method survey undertaken this spring about the future of Acadian dykelands in Nova Scotia in the face of climate change. The new multiple-reminder survey about farm management on marginal land in Nova Scotia is in the design phase, and I am also writing a proposal for baseline social research to be undertaken prior to the restoration of the Big Marsh Bog on Brier Island, drained back in the 1950s. Finally, as Academic Program Coordinator here at SRES, I am leading a review of our internship-based Master of Resource and Environmental Management, and our alumni survey is still in the field. This doesn’t include my peripheral engagement in quantitative survey and Q-method work led by others, for instance, around energy knowledge and discourses. If this is not a methodological blip, I will need to polish up my stats skills.

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