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Record W3000601470 · doi:10.3390/su12020498

Intergenerational Dialogue, Collaboration, Learning, and Decision-Making in Global Environmental Governance: The Case of the IUCN Intergenerational Partnership for Sustainability

2020· article· en· W3000601470 on OpenAlexaff
Melanie Zurba, Dominic Stucker, Grace Mwaura, Catie Burlando, Archi Rastogi, Shalini Dhyani, Rebecca Koss

Bibliographic record

VenueSustainability · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsDalhousie University
Fundersnot available
KeywordsIUCN Red ListGeneral partnershipSustainabilityCorporate governanceGrassrootsEnvironmental governancePolitical scienceSociologyPublic relationsEnvironmental resource managementEnvironmental planningPublic administrationEconomicsManagementEcologyGeographyBiologyLaw

Abstract

fetched live from OpenAlex

This article provides evidence and a rationale based on adaptive governance studies for why creating meaningful youth engagement should be understood in terms of intergenerational dialogue, collaboration, learning, and substantive decision-making in global environmental governance. We have centered our discussion on the International Union for the Conservation of Nature (IUCN), as the largest global conservation organization. Through an organizational ethnography approach, we have demonstrated how generational concerns within the IUCN have been framed in terms of participation, and then present the IUCN Intergenerational Partnership for Sustainability (IPS) as a case study of a grassroots movement that is focused on transforming the IUCN towards being a fully intergenerational global governance system for nature conservation. We have described the development of intergenerational thinking and action within the IUCN, and discussed intergenerational governance as being essential for addressing nature conservation challenges faced by local communities in times of increasing global uncertainty. We conclude by providing recommendations for enhancing intergenerational dialogue and building intergenerational governance structures within global conservation organizations.

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.

How this classification was reachedexpand

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)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.010
GPT teacher head0.281
Teacher spread0.272 · 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

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations22
Published2020
Admission routes1
Has abstractyes

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