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🌻 Shaun's case study
23 Jun 2026

Shaun Finnetty used Causal Map to analyse interview data for his PhD thesis on court reform in Belize. Causal mapping let him operationalise critical realism, the meta-theoretical approach behind his research, and trace institutional change back to the causal claims made by the people living through it.

The researcher Shaun Finnetty is a PhD researcher at the University of Bath. His thesis examines how, why and to what extent court performance management (CPM) policies and practices contributed to institutional change in the Belizean judiciary between 2018 and 2022. Focused on a resource-constrained court system, the research addresses a gap in our understanding of CPM implementation dynamics and institutional evolution in small developing states.

Shaun's research set out to answer:

Box 1: Research questions

  1. How was CPM conceptualised in the Belizean context between 2018 and 2022?
  2. Why, how and to what extent did CPM in the Belizean judiciary evolve from a traditional legal approach to a managerial, efficiency-focused one during the study period?
  3. What were the CPM implementation dynamics and their effects when using case backlog reduction as a focused outcome?
  4. Why, how and to what extent did CPM policies and practices drive institutional change in the Belizean judiciary during the study period?

Critical realism, the meta-theoretical approach underpinning Shaun's thesis, is centrally concerned with causality and generative mechanisms. Causal mapping gave him a way to operationalise that focus directly, rather than treating it as a background assumption.

"It allowed for the comprehensive cataloguing, coding and visualising of causal claims from interview data. This approach revealed the dominant mental models of interviewees regarding CPM implementation dynamics. By focusing on causal interconnections rather than only distilling themes, a systems-based understanding of occurrences was developed, allowing for explanation instead of description."

Analysis you can trace back to the data#

Every causal claim in Shaun's map links back to the original interview quotation that supports it.

"This strengthens the research's soundness and trustworthiness by making the analytical process more rigorous, transparent and verifiable."

He used the Causal Map app to move between individual interview maps and one aggregated master map of the whole dataset, applying the app's filters to run more targeted analyses, and pulling descriptive statistics from the master map to spot patterns across the interviews.

shaun's map Looking back at the project as a whole, Shaun summed up what causal mapping gave him that a more conventional approach wouldn't have:

"Using the Causal Map application as specialised software allowed for the effective and efficient execution of the causal mapping approach, and was helpful in organising and understanding causal relationships in the interview data."

— Shaun Finnetty, PhD researcher, University of Bath