Toward a post-carbon society: supporting agency for collaborative climate action
Bibliographic record
Abstract
Current post-carbon transition trajectories are primarily focused on external solutions, while citizens’ inner lives and roles in collective transformation and system change processes are largely overlooked. To address this gap, this study aims to explore the potential role of citizens as active agents of change. Specifically, it examines how citizens perceive and address climate change, the factors that can empower and motivate them to act, and how they imagine future transformation pathways and their own role within them. Based on a combined SenseMaker and Grounded Theory methodology, we explore citizens’ perspectives and discuss their implications for improving current approaches and discourses, such as lifestyle environmentalism and post-growth. Our findings provide important insights into the interplay between people’s motivation, sense of agency, and social paradigms, with direct implications for policy and practice. They show that the materialistic growth paradigm under which most people act does not support motivation and engagement in sustainability transformations. Secondly, although intrinsic motivation, along with values such as care and community, increase engagement and transformation, they are seldom reflected in current policy approaches and discourses. Thirdly, a sense of agency is key for lasting individual and collective engagement. Put together, the results indicate that empowering individual and collective agency requires challenging current societal and systemic values that lie at the root of today’s crises. Supporting conditions that allow the emergence of new social paradigms through targeted actions at individual, collective, and system levels is thus crucial to tackling climate change and meeting policy targets.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.033 |
| Scholarly communication | 0.018 | 0.016 |
| Open science | 0.002 | 0.021 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".