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Record W2785337431 · doi:10.23865/arctic.v9.729

The Rationale for the Duty to Consult Indigenous Peoples: Comparative Reflections from Nordic and Canadian Legal Contexts

2018· article· en· W2785337431 on OpenAlexaboutno aff
Christina Allard

Bibliographic record

VenueArctic review on law and politics · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean and International Law Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousDutyParliamentPolitical scienceLawInternational lawPolitics

Abstract

fetched live from OpenAlex

Although the standard of consulting Indigenous peoples in decisions affecting them is well rooted internationally as well as in national legal systems, different views and patterns of problems are associated with the concept and its practice. This paper briefly analyses and contrasts the duty to consult Indigenous peoples through a comparison of the three Nordic countries Norway, Finland and Sweden, and Canada. Based on domestic legal sources, the focus of the paper is to explore the legal foundation that has given rise to the specific set of rules for the duty to consult, that is, the rationale behind the evolving of the rules. The first finding is that the rules differ among the three Nordic countries, with Sweden being the only country that lacks specific rules. Secondly, whereas Canada has developed its own duty to consult primarily through domestic case law, in the Nordic countries, duty to consult is related to international law obligations. Consultation duties that have evolved from domestic law may be easier to accept than “foreign” regulations imposed on national legal systems. This could explain the reluctance among the Nordic States to accept specific consultations with the Sami Parliament and other Sami groups, particularly in Sweden.

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)0.014
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.115
Threshold uncertainty score0.833

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0060.009
Science and technology studies0.0260.029
Scholarly communication0.0130.004
Open science0.0020.005
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.075
GPT teacher head0.385
Teacher spread0.310 · 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 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

Citations32
Published2018
Admission routes1
Has abstractyes

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