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Record W7027198937

Call for Inputs: Climate Change and Human Rights: A Safe Climate

2019· article· en· W7027198937 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsnot available
Fundersnot available
KeywordsHuman rightsCLARITYEnvironmental lawNova scotiaClimate changeGeneral assemblyThematic analysisInternational law
DOInot available

Abstract

fetched live from OpenAlex

There is now global agreement that human rights norms apply to the full spectrum of environmental issues, including climate change. The previous Special Rapporteur on human rights and the environment, Mr. John Knox, developed Framework Principles on Human Rights and the Environment that set forth three sets of duties that engage both States and businesses: procedural obligations; substantive obligations; and obligations relating to those in vulnerable situations.\nThe current Special Rapporteur on human rights and the environment, Mr. David Boyd, is working to provide additional clarity regarding the substantive obligations relating to a range of elements that are essential to the enjoyment of a safe, clean, healthy and sustainable environment. His first report to the Human Rights Council addressed air pollution and associated obligations. He is now preparing a thematic report focusing on human rights obligations related to global climate change. For that purpose, he is seeking inputs on the topic from States and stakeholders through responses to the brief questionnaire below.\nYour replies will inform the Special Rapporteur’s analysis and contribute to his report, which will be presented to the General Assembly in October 2019.\nQuestionnaire submission by:\nSara L Seck, Associate Professor, Marine & Environmental Law Institute, Schulich School of Law, Dalhousie University, Nova Scotia Canada Sara.Seck@dal.ca\nAnd\nLisa Benjamin, post-doctoral fellow, Marine & Environmental Law Institute, Schulich School of Law, Dalhousie University, Nova Scotia Canada Lisa.Benjamin@dal.ca

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)0.004
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.391
Threshold uncertainty score0.869

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0070.002
Scholarly communication0.0100.006
Open science0.0020.006
Research integrity0.0200.010
Insufficient payload (model declined to judge)0.3910.129

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 head0.024
GPT teacher head0.296
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 source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2019
Admission routes1
Has abstractyes

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