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Record W7000052764

The Ends and The Means: Indigenous Sovereignty, Climate-Related Legal Actions, and Frameworks of Justice

2022· article· en· W7000052764 on OpenAlexaboutno aff

Bibliographic record

VenueProject Muse (Johns Hopkins University) · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Circumstantial evidencePopulationPretextSubject (documents)Insignificance
DOInot available

Abstract

fetched live from OpenAlex

Philosophy professor Timothy Morton uses climate change as his foremost example of what he calls a hyperobject: an object that occupies both more physical space and more time than humans can usefully comprehend. For example, one can understand local meteorological occurrences in isolation without necessarily understanding that a given storm was more severe than it should have been because an overall increase in global temperatures makes for a more aggressive, active hydrological cycle. Environmental organizations focused on raising awareness understand this. Public campaigns to wed the nebulous idea of climate change to specific, concrete images are incredibly memorable: think of a polar bear struggling to stand on a diminished iceberg. In light of climate change's unique status as a problem, it may seem more reasonable that climate change has yet to meet its ideal legal match regarding causes of action; climate change is too large and too slow-moving to be tackled by traditional schools of thought within the law. Indeed, the number of countries that have recognized a justiciable cause of action for climate change are far outweighed by countries that have not.\nClimate change activist groups often pursue multiple legal approaches and appeal to multiple levels of authority worldwide, as there are many imperfect options available. Indigenous nations, depending on the country in which they are contained, may have treaty-based or otherwise more specific causes of action available for climate-related legal actions. An examination of currently ongoing climate litigation that features Indigenous parties in the United States, Canada, New Zealand, and Argentina provide insight into how Indigenousspecific domestic legal approaches may shape climate-related adjudication going forward.

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: none
Teacher disagreement score0.957
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.013
GPT teacher head0.244
Teacher spread0.231 · 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
Published2022
Admission routes1
Has abstractyes

Explore more

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