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Record W3091943043

Indigenous Rights, Political Mobilisation and Indigenous Control over Development: Natural-Gas Processing in Western Australia

2015· book-chapter· en· W3091943043 on OpenAlexaboutno aff
Ciaran O’Faircheallaigh

Bibliographic record

VenueGriffith Research Online (Griffith University, Queensland, Australia) · 2015
Typebook-chapter
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousIndigenous rightsPolitical sciencePoliticsPossession (linguistics)Human rightsLegislationConventionGeographyLawEnvironmental protectionEcology
DOInot available

Abstract

fetched live from OpenAlex

Since the early 1970s, there has been a trend towards growing formal recognition of indigenous rights in international forums and in many states with significant indigenous populations; Given that the continued possession and control of their ancestral lands is central to the survival and wellbeing of indigenous peoples, recognition of indigenous interests in land and sea has been central to the movement for recognition of indigenous rights. In the international arena, the principle of Indigenous Free Prior Informed Consent (lFPIC), which asserts that indigenous peoples must decide whether development occurs on their ancestral estates, and the nature of any development that does occur, has increasingly been reflected in international treaties and declarations, including the International Convention on Biodiversity (2002) and the UN Declaration on the Rights of Indigenous People (2007). At the national level, constitutional enactments or legislation providing for recognition of indigenous rights in land has been introduced in countries as diverse as Australia, Canada, New Zealand, the Philippines, Nicaragua and Colombia.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.089
GPT teacher head0.320
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2015
Admission routes1
Has abstractyes

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