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Record W4253489645 · doi:10.24124/2019/59046

The importance of land and water to the culture of the Xeni Gwet’in First Nation : an analysis of statements presented at environmental impact assessment hearings

2019· dissertation· en· W4253489645 on OpenAlexfundno aff
Tashi Yang Chung Sherpa

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
FundersGovernment of CanadaAustralian Government
KeywordsIndigenousIdentity (music)SociologySocial scienceEcology

Abstract

fetched live from OpenAlex

An application for a new open-pit gold/copper mine in Tsilhqot’in territory raised concerns among the local Xeni Gwet’in people about potential impacts. This study examines statements about these concerns and potential impacts made by Xeni Gwet’in people during environmental assessment hearings. The research adopts a single case study approach, and the analysis uses a western social science method as well as a more holistic Indigenous approach to decolonizing research by placing Indigenous voices in the center of the research process. The results suggest that land and water are inseparable, as are their connections to the Xeni Gwet’in people, culture, and territory. Key findings include that land and water are central to Xeni Gwet’in identity and future, that they are used to demonstrate ‘control’ and ‘ownership’ of their traditional territory, and that they are crucial to Xeni Gwet’in intergenerational transfer of knowledge, culture, and sacred spiritual connections to their traditional territory.

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)0.002
metaresearch head score (Gemma)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.983
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.008
Scholarly communication0.0030.002
Open science0.0000.004
Research integrity0.0010.001
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 head0.012
GPT teacher head0.356
Teacher spread0.344 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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