Policy Innovations for a Green Transition (PIGT)

Policy Innovations for a Green Transition (PIGT) - combinespolicy theory with Al algorithms to explain and predict policy changes in the minerals, energy and forestry sectors.

This project recognizes the tangible need for policy innovations that enable the green transition and aims to explain and predict policy change. The aim is to learn about how different factors, such as transformative events, policy learning and negotiations, shape the public policy process, and further to identify indicators of when a policy change will take place. Social science methods are combined with AI algorithms and natural language models to analyse the stability and changes in Swedish policies for minerals, energy and forests over the last 30 years. The project will contribute with new empirical insights into the policy dynamics in the studied sectors, develop new methods at the intersection of policy science and AI, and finally generate state-of-the-art knowledge on drivers and barriers to policy changes and innovations needed for a more sustainable future.

One person working on the project is Felicia Robertsson, a postdoctoral researcher.

Where are you originally from, and what is your academic background?

I grew up in Luleå but I have studied in Strasbourg, France, Umeå, Sweden, Canada and Gothenburg, Sweden. I received my PhD in Political Science from the University of Gothenburg in September 2023. In my dissertation, I studied what affects the general public’s trust assessment of political institutions. My background is in measuring political attitudes and opinions using various statistical techniques.

What is the main focus of your research within the project?

I work on the SUN financed project Policy Innovations for a Green Transition - Combining Policy Theory with Al to Explain and Predict Policy Change. My main focus is on the attitudes and beliefs of actors involved in policy-making and what makes them change. Within the project I am in charge of collecting data on parliamentary debates, policy documents, and media articles to capture attitudes and to analyse how attitudes and beliefs change over time.

What attracted you to this specific research project?

I applied for this position because it was a unique opportunity to improve my methodological skills in machine learning applied to interesting and contentious political issues of natural resource use. I also found it intriguing to center on attitudes of policy-makers instead of the general public, since policy-makers drive or hinder policy change that has an effect on the ground.

What are some of the key research questions or objectives you're focusing on during your post-doc?

The research question that I am focusing on is 1) What periods of policy stability and change characterize Sweden's energy and mineral policy from 1990 to 2024, 2) How can the policy change be explained by alternations in a) political institutions, b) the occurrence of events, and c) revisions in policy actors' beliefs, and 3) How can AI technology, and the use of analytical algorithms and machine learning, advance theory development in the political- and policy sciences?

Are there any specific skills or knowledge areas you aim to enhance during your time on the project?

I aim to advance my skills in computational text analysis to study political science problems. I also want to deepen my knowledge regarding resource management in a country comparative perspective.

How do you envision the findings of this project making an impact, either locally or globally and how do you think this post-doc project can contribute to the goal of the Green Transition?

Sweden and the world currently prepare to undertake a major push towards a green transition to meet the goals of both international agreements and national environmental goals. However, sustainability transitions also spur critical issues, not the least concerning the extraction and use of natural resources, that give rise to intractable conflicts among actors and interests that need to be handled politically. Thus, while technological innovations spanning across a multitude of sectors are imperative to accomplish such far-reaching transitions, innovations in public policy are equally, or even more, important. A more sustainable future requires a public policy mix that enables long-term industrial investments and technological changes, as well as support and facilitate the subsequent societal transitions by handling conflicts of goals and interests. New policy should thus meet the requirements of simultaneously being effective, cost-efficient, and publicly accepted, which require new policy innovations and thereby significant policy change. We know from the literature how single policies should be designed to confirm with one or several of the above requirements but significantly less is known about how such policy change come about in the first place. Knowing how critical policy change come about are important lessons are not only for Sweden, but also to the rest of the world as well. Hence, the project will contribute with novel empirical insights on policy process dynamics, develop new methods at the intersect of social sciences and AI algorithms, and generate theoretical knowledge about drivers and obstacles to disputed policy change.

What unique challenges or opportunities do you anticipate working in the northern Sweden?

The distance to other researchers studying policy change using text-as-data approaches is vast, which means I must travel or schedule online meetings more than before. On the other hand, conducting a technically demanding project at a technical university means that we possess most skills in-house. Likewise, a majority of researchers at the social science section at LTU specializes in natural resource management, which means that we get a lot of useful feedback on the policy areas we study.