Political economics, collective action and wicked socio-ecological problems: A practice story from the field
Bibliographic record
Abstract
Empowering integrative, sustainable and equitable approaches to wicked socio-ecological problems requires multiple disciplines and ways of knowing. Following calls for greater attention to political economics in this transdisciplinary work, we offer a practitioner perspective on political economy and collective action and their influences on our community engagement practice and public policy. Our perspective is grounded in a pervasive wicked problem in Australia, invasive rabbits, and the emergence of the Victorian Rabbit Action Network. The network grew out of a publically funded research project to support community-led action in rabbit management. Victorian residents and workers affected by rabbits – public and private land managers, scientists, government officers and others – were invited to engage in a participatory planning process to generate sustainable strategies to address the rabbit problem. Each stage in the process, which involved interviews, a workshop and consultations, was designed to nurture the critical enquiry, listening and learning skills of participants, advance understandings of the problem from multiple perspectives, generate collective options to guide decision-making, and encourage community-led collective action. We reflect on our understanding of these processes using the language and lens of political economics and, in particular, the context of democratic professionalism. In so doing, we define terms and refer to information resources that have enabled us to bring a practical working knowledge of political economics to our professional practice. Our intent is to motivate academics, community members, government officials, and scientists alike, to draw on their knowledge and field experiences and to share practice stories through the lens of political economics and collective action. This is an opportunity to engage each other in small ‘p’ politics of how we understand and act on wicked problems, to negotiate and connect across disciplines, practical experiences and human difference, so that people may work more creatively and effectively together to address the challenging issues of our time.
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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 | 0.045 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.044 | 0.106 |
| Scholarly communication | 0.027 | 0.026 |
| Open science | 0.004 | 0.024 |
| Research integrity | 0.018 | 0.024 |
| Insufficient payload (model declined to judge) | 0.003 | 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".