Attitudinal Research

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Understanding why climate policies generate support or resistance requires moving beyond demographic analysis to examine the underlying values, identities, and belief systems that shape people's responses. Standard opinion polling captures surface-level preferences but often lacks the methodological rigour to identify causal relationships or distinguish between different types of opposition.

I design and deliver attitudinal research projects using advanced quantitative methods including survey design, stratified sampling, factor analysis, structural equation modeling, and path analysis. This research identifies not just who opposes climate policy, but why they oppose it - and critically, reveals the different pathways to resistance among groups that might appear similar on the surface.

What I offer:

Survey Design and Data Collection Design of measurement instruments using validated scales, pilot testing, and full-scale data collection with stratified random sampling to ensure representativeness. This includes questionnaire design that avoids common pitfalls, and sampling strategies that achieve appropriate demographic and political representation.

Factor Analysis and Scale Development Development of new measurement instruments through exploratory and confirmatory factor analysis. This includes identifying the underlying dimensions of complex attitudes (such as different types of climate policy resistance), testing scale reliability and validity, and creating tools that can be used in future research or policy evaluation.

Structural Equation Modelling and Path Analysis Analysis of causal relationships between attitudes, identities, and policy preferences using structural equation modeling. This reveals not just correlations but the pathways through which variables influence each other 

Q-Sort Methodology Design and analysis of Q-Sort studies to identify distinct subjective viewpoints within a population. Unlike surveys that measure agreement with individual statements, Q-Sort forces participants to rank competing priorities against each other, revealing genuine value trade-offs rather than abstract preferences. Statistical analysis identifies clusters of participants who share similar perspectives, providing a nuanced picture of competing viewpoints that policymakers must navigate.

Research outputs:

Research reports suitable for internal or external policy briefings for decision-makers, and practical guidance on how findings should inform policy design and communications strategy. All research is conducted to academic standards with full transparency about methods, limitations, and analytical choices.