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Record W2978502873 · doi:10.11575/prism/36805

The Right to Be Cold: Examining the Indigenous Peoples’ Rights and Climate Change

2019· dissertation· en· W2978502873 on OpenAlexaboutno aff
Dayo Adeniyi Ogunyemi

Bibliographic record

VenueOpen MIND · 2019
Typedissertation
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousClimate changePolitical scienceEnvironmental ethicsGeographyDevelopment economicsEcologyGeologyEconomicsPhilosophyOceanography

Abstract

fetched live from OpenAlex

The reality of climate change and its adverse implication on the human and environmental rights of the Inuit is no longer in doubt. The observed impacts of climate change in the Arctic region confirm that the change in climate has violated the fundamental human rights of the Inuit inhabiting the Arctic region, the integrity of the Arctic ecosystem, and also the environmental “right to be cold”. Emissions of greenhouse gases primarily due to human activities have contributed monumentally to climate change, and these emissions have, over the years, been encouraged by the actions or inactions of States. The principle that “where there is a right, there is a remedy” prompts the search for legal remedies within the international human rights system to address the impacts of climate change on the Inuit and the Arctic region. This thesis addresses the legal and regulatory framework that can be adopted to address the impact of climate change on Northern Indigenous peoples. The question of whether current global regimes on climate change provide an effective mechanism for the Peoples of the Arctic to seek redress to defend their culture and way of life is also addressed. This thesis argues that the Inuit may find an effective mechanism to seek redress within the existing United Nations and Inter-American human rights systems.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.962
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.043
GPT teacher head0.341
Teacher spread0.298 · 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.

Study designNot applicable
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

Citations2
Published2019
Admission routes1
Has abstractyes

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