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Record W4391012343 · doi:10.1017/s2047102523000201

Rights of Nature on the Island of Ireland: Origins, Drivers, and Implications for Future Rights of Nature Movements

2024· article· en· W4391012343 on OpenAlexfundno aff
Rachel Killean, Jérémie Gilbert, Peter Doran

Bibliographic record

VenueTransnational Environmental Law · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsnot available
FundersQueen's UniversityUniversity of SydneyQueen's University Belfast
KeywordsPoliticsHuman rightsContext (archaeology)Political scienceCorporate governanceEnvironmentalismEnvironmental ethicsEnvironmental governanceSociologyLawGeographyBusiness

Abstract

fetched live from OpenAlex

Abstract Over the course of 2021, several local councils across the island of Ireland introduced motions recognizing the ‘Rights of Nature’. To date, little research has been conducted into these nascent Rights of Nature movements, even though they raise important questions about the philosophical, cultural, political, and legal drivers in pursuing such rights. Similarly, much remains unclear as to the implications of such initiatives, both in their domestic context and for Rights of Nature movements around the world. This article contributes to addressing this gap by exploring these themes through an analysis of interviews with key stakeholders conducted across the island of Ireland in June 2022. In particular, it explores the impact of international movements, colonial legacies, cultural heritage, and years of inadequate environmental governance, in motivating local councils to pursue a Rights of Nature strategy.

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 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)0.006
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.015
Scholarly communication0.0080.006
Open science0.0010.006
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.005
GPT teacher head0.260
Teacher spread0.255 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations10
Published2024
Admission routes1
Has abstractyes

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