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Record W2337340546

Climate Change and Human Rights: How? Where? When?

2015· article· en· W2337340546 on OpenAlexaff
Basil Ugochukwu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsCentre for International Governance Innovation
Fundersnot available
KeywordsHuman rightsLivelihoodClimate changePolitical economy of climate changePolitical scienceNegotiationInternational human rights lawEnvironmental planningEnvironmental resource managementDevelopment economicsGeographyEconomicsLawAgricultureEcology
DOInot available

Abstract

fetched live from OpenAlex

Climate change poses a threat to several internationally recognized human rights, including the rights to food, a livelihood, health, a healthy environment, access to water and the rights to work and to cultural life. Actions taken to mitigate and adapt to the adverse impacts of climate change have to be centred on human rights. In negotiations for a binding international climate change instrument, nation states have been called upon to fully respect human rights in all climate-related actions. As important as this demand is, there is also the need to describe and plan how human rights can be integrated into international, national, subnational and corporate climate change strategies. This paper analyzes a few examples of national, subnational and corporate climate change policies to show how they have either enshrined human rights principles, or failed to do so.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.040
Scholarly communication0.0090.013
Open science0.0010.005
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0060.001

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 head0.082
GPT teacher head0.325
Teacher spread0.242 · 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 designTheoretical or conceptual
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

Citations3
Published2015
Admission routes1
Has abstractyes

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