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Record W3126386335 · doi:10.14430/arctic72299

The Relationship between Kanngiqtugaapik/Clyde River and Greenpeace: An Interview with Mayor Jerry Natanine

2021· article· en· W3126386335 on OpenAlexvenueaboutno aff
Danita Catherine Burke

Bibliographic record

VenueARCTIC · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental ethicsArt historyArtGeographyPhilosophy

Abstract

fetched live from OpenAlex

For six years the Town of Kanngiqtugaapik/Clyde River, Nunavut, Canada battled Canada’s National Energy Board (NEB) about its approval for seismic testing near the community (Tasker, 2017). The NEB regulates “pipelines, energy development and trade in the Canadian public interest” (National Energy Board, 2018) but in this case the NEB stood accused of circumventing the public interest of the community and failing to do proper, and mandatory, consultation with the community and its Inuit land claim beneficiary residents. In a landmark series of events, the people of Kanngiqtugaapik/Clyde River partnered with Greenpeace to challenge the NEB in the Supreme Court of Canada. On the 26 July 2017 the Supreme Court of Canada ruled that the community’s argument that the “proposed testing could negatively affect the treaty rights of the Inuit of Clyde River, who opposed the seismic testing, alleging that the duty to consult had not been fulfilled in relation to it” would be upheld (Supreme Court Judgments, 2017). On the 19th December 2018, I had an opportunity to talk by telephone with Mr. Jerry Natanine, Mayor of Kanngiqtugaapik /Clyde River. Mr. Natanine led the effort to protect his community and have Inuit treaty rights respected by the NEB. The following is a transcript of our conversation and his insights into the working relationship with Greenpeace, how it developed, and what role it played in assisting the efforts of Kanngiqtugaapik/Clyde River to have its rights respected.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.698

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.026
GPT teacher head0.227
Teacher spread0.201 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2021
Admission routes2
Has abstractyes

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Same venueARCTICSame topicAmerican Environmental and Regional HistoryFrench-language works237,207