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Record W4416868098 · doi:10.14237/ebl.16.2.2025.1914

Threats to Heritage in Cultural Keystone Places: Fitting Western Concepts into Gitxsan Legal Orders and Laws

2025· article· W4416868098 on OpenAlexaffabout
Ardythe Wilson Dimdiigibuu, Chelsey Geralda Armstrong

Bibliographic record

VenueEthnobiology Letters · 2025
Typearticle
Language
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsStewardship (theology)Cultural heritageCultural heritage managementContext (archaeology)ValuesFace (sociological concept)Work (physics)Keystone species

Abstract

fetched live from OpenAlex

Resource extraction poses significant threats to cultural heritage sites and landscapes across British Columbia (BC, Canada), particularly in Gitxsan Territories, where people’s values are often overlooked in archaeological heritage management and consulting contexts. This research explores how Gitxsan legal orders and stewardship principles can contribute to conserving and restoring culturally and ecologically significant places—crucial work in the face of ongoing colonial policies and an increasingly changing climate. Cultural landscapes, characterized by the Lax’yip (Gitxsan Wilp/House Territories), provide a foundation for understanding long-standing stewardship practices and relationships that underscore cultural and environmental values and well-being. A key challenge, however, is how to effectively represent these landscapes to outsiders who may not share the same cultural connections to the land or understand Gitxsan heritage, histories, laws, and protocols. Reviewing these tensions in the context of resource extraction in one Territory, Lax Xsin Djihl, Wilp/House histories and stewardship practices are routinely ignored by archaeological consultants, leading to the destruction of cultural heritage. Evocative metaphors, such as cultural keystone places, may offer a way to convey the ecological and cultural realities of Territories for Gitxsan Houses, fostering a broader understanding and deeper regard for Gitxsan cultural heritage within archaeological regulatory frameworks.

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)0.003
metaresearch head score (Gemma)0.005
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: none
Teacher disagreement score0.462
Threshold uncertainty score0.929

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0150.075
Scholarly communication0.0150.006
Open science0.0020.008
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.053
GPT teacher head0.319
Teacher spread0.266 · 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
Published2025
Admission routes2
Has abstractyes

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