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Record W4226169891 · doi:10.1093/biosci/biac031

Governing for Transformative Change across the Biodiversity–Climate–Society Nexus

2022· article· en· W4226169891 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

VenueBioScience · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsFisheries and Oceans CanadaUniversity of British Columbia
Fundersnot available
KeywordsTransformative learningNexus (standard)Climate changeCorporate governanceBiodiversityEnvironmental resource managementPolitical scienceEnvironmental planningEnvironmental ethicsEcologyBusinessSociologyGeographyEconomicsEngineeringBiology

Abstract

fetched live from OpenAlex

Abstract Transformative governance is key to addressing the global environmental crisis. We explore how transformative governance of complex biodiversity–climate–society interactions can be achieved, drawing on the first joint report between the Intergovernmental Panel on Climate Change and the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services to reflect on the current opportunities, barriers, and challenges for transformative governance. We identify principles for transformative governance under a biodiversity–climate–society nexus frame using four case studies: forest ecosystems, marine ecosystems, urban environments, and the Arctic. The principles are focused on creating conditions to build multifunctional interventions, integration, and innovation across scales; coalitions of support; equitable approaches; and positive social tipping dynamics. We posit that building on such transformative governance principles is not only possible but essential to effectively keep climate change within the desired 1.5 degrees Celsius global mean temperature increase, halt the ongoing accelerated decline of global biodiversity, and promote human well-being.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.495
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.042
GPT teacher head0.261
Teacher spread0.219 · 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