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Record W3189798995 · doi:10.1038/s41893-021-00755-x

Six modes of co-production for sustainability

2021· article· en· W3189798995 on OpenAlexaff
Josephine M. Chambers, Carina Wyborn, Melanie Ryan, Robin S. Reid, Maraja Riechers, Anca Şerban, Nathan Bennett, Christopher Cvitanovic, María E. Fernández‐Giménez, Kathleen A. Galvin, Bruce Evan Goldstein, Nicole Klenk, Maria Tengö, Ruth Brennan, Jessica Cockburn, Rosemary Hill, Claudia Múnera‐Roldán, Jeanne Nel, Henrik Österblom, Angela Bednarek, Elena M. Bennett, Amos Brandeis, Lakshmi Charli-Joseph, Paul Chatterton, Kent E. Curran, Pongchai Dumrongrojwatthana, América Paz Durán, Salamatu J. Fada, Jean‐David Gerber, Jonathan Green, Angela M. Guerrero, Tobias Haller, Andra‐Ioana Horcea‐Milcu, Beria Leimona, Jasper Montana, Renée Jane Rondeau, Marja Spierenburg, Patrick Steyaert, Julie G. Zaehringer, Rebecca L. Gruby, Jon Hutton, Tomas Pickering

Bibliographic record

VenueNature Sustainability · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsUniversity of TorontoMcGill UniversityUniversity of British Columbia
FundersEconomic and Social Research CouncilCambridge Conservation InitiativeLuc Hoffmann InstituteNiedersächsisches Ministerium für Wissenschaft und KulturWalton Family FoundationRhodes UniversityUK Research and InnovationPew Charitable TrustsSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungLeverhulme TrustGordon and Betty Moore FoundationNational Science FoundationMAVA FoundationDavid and Lucile Packard Foundation
KeywordsCognitive reframingSustainabilityProduction (economics)Diversity (politics)CLARITYAgency (philosophy)Sustainable developmentEnvironmental resource managementBusinessPolitical scienceSociologyEcologyPsychologySocial scienceEconomics

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaScience and technology studies
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
gptno category
Domain: not available · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
models splitAgreement compares identical category sets and study designs across arms.

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.998
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0020.011
Scholarly communication0.0080.008
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0270.002

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 head0.010
GPT teacher head0.298
Teacher spread0.288 · 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

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

Science and technology studies

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical · Methods

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".

Quick stats

Citations499
Published2021
Admission routes1
Has abstractno

Explore more

Same venueNature SustainabilitySame topicSustainability and Climate Change GovernanceCategoryScience and technology studiesFrench-language works237,207