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Record W2950429336 · doi:10.5130/ijcre.v12i1.6496

Political economics, collective action and wicked socio-ecological problems: A practice story from the field

2019· article· en· W2950429336 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGateways International Journal of Community Research and Engagement · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCommunity Development and Social Impact
Canadian institutionsUniversity of Northern British Columbia
FundersAustralian GovernmentAgriculture VictoriaU.S. Department of Agriculture
KeywordsCollective actionPublic relationsGovernment (linguistics)PoliticsWicked problemContext (archaeology)SociologyParticipatory action researchPolitical scienceManagementEconomicsLaw

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.242
GPT teacher head0.396
Teacher spread0.154 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it