Text Analysis

Inferential reasoning and abductive approaches to policy analysis under uncertainty 

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by M. Ramesh and Michael Howlett

Policy analysis is often expected to deliver clear, evidence-based recommendations. Yet many contemporary policy problems—from climate change to pandemics—are characterised by uncertainty, complexity, and disagreement about both facts and values. In their recent article, Inferential Reasoning in Policy Analysis: Knowledge Use under Uncertainty and Complexity, M. Ramesh and Michael Howlett examine how policy analysts can generate useful advice under these conditions and argue for a greater role for inferential and abductive reasoning in policy analysis. 

The limits of conventional policy analysis 

Much traditional policy analysis assumes relatively stable conditions in which analysts can gather reliable evidence, clearly define policy problems, and evaluate options using established tools such as cost–benefit analysis or impact assessment. Ramesh and Howlett suggest that these assumptions often break down in contemporary policy environments. 

Many policy challenges combine empirical uncertainty with political disagreement and strong value conflicts. Under such conditions, technical analytical tools may struggle to produce timely or actionable guidance. At the same time, approaches that rely primarily on participatory deliberation can face different challenges, including difficulties integrating empirical evidence into decision-making. 

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Highlights collection from Policy & Politics: free to access from 1st May – 31st August 2026 on Environmental policy through theory: collaboration, narratives, evidence and design 

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by Allegra Fullerton (Digital Associate Editor) and Sarah Brown (Senior Journals Manager)

The articles featured here demonstrate how collaborative governance, policy narratives, evidence use and policy design shape environmental policy, revealing how coordination, meaning, knowledge and calibration interact to influence policy targets, implementation pathways and outcomes. What links the four contributions is not only their theoretical pluralism but also a shared methodological ambition: each pushes an established policy process framework in new empirical directions, drawing on approaches ranging from evolutionary game modelling to natural language processing and multilevel Bayesian regression.  

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Evidence use in pesticide policymaking

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by Ueli Reber, Karin Ingold and Christian Stamm

Swiss lawmakers have debated pesticide regulation for nearly a decade, often drawing on different types of scientific and policy evidence to support their positions. In Reber et al.’s recent study, the authors analyse how problemoriented evidence (highlighting environmental or health risks) and solutionoriented evidence (emphasising policy effectiveness) were used strategically in parliamentary discussions. 

Analysing parliamentary texts with computational methods 
To study this, the authors compiled a corpus of 1,738 parliamentary documents — including written requests and plenary debate transcripts — containing references to pesticides. Using keyword searches, they retrieved 10,642 paragraphs. They then applied finetuned transformerbased text classification models to each paragraph to classify (1) the position expressed — either in favour of policy change (“change”) or defending existing policy (“status quo”) — and (2) whether the paragraph invoked evidence, and if so whether that evidence was problemoriented (highlighting risks) or solutionoriented (emphasising the effectiveness or sufficiency of existing or alternative policy measures). 

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How Policy Narratives Shape Sustainability Governance: A Case Study of Urban Transport Policy Discourse 

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This article investigates how policy narratives shape sustainability governance, by examining sustainability imaginaries and macrolevel narratives in urban transport policy through the lens of the Narrative Policy Framework. It examines how sustainability policy is shaped not only by institutions and interests, but by the stories actors tell about the future. Focusing on sustainability governance, it argues that policy processes are structured by competing macrolevel narratives that articulate different understandings of what sustainability means and how it should be pursued. 

The article brings together two bodies of scholarship that are often treated separately: sustainability science-based research on sustainable imaginaries, and policy process theory, particularly the Narrative Policy Framework (NPF). Sustainability, the authors argue, is inherently normative and future-oriented. It begins as a vision of a desirable future before being translated into policy action, and these visions are continually reworked through policy discourse. 

Building on work by Adloff and Neckels, the authors conceptualise three ideal-typical sustainability trajectories — modernization, transformation and control — and translate them into sustainability policy paradigms. Drawing on Stauffer’s account of macrolevel narratives as policy paradigms “in story form”, they show how each paradigm is underpinned by distinct cultural and institutional narratives. 

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