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Record W2791591215 · doi:10.1215/00141801-4260674

The Rock Painting/Xela:ls of the Tsleil-Waututh: A Historicized Coast Salish Practice

2018· article· en· W2791591215 on OpenAlexaff
Chris Arnett, Jesse Morin

Bibliographic record

VenueEthnohistory · 2018
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPaintingCreaturesRock artShoreHistoryEthnographyAncient historyArchaeologyArt historyGeologyNatural (archaeology)Oceanography

Abstract

fetched live from OpenAlex

Abstract This article argues that the red-ocher paintings (pictographs) in Coast Salish Tsleil-Waututh territory in Indian Arm, British Columbia, were made around the time of contact in specific response to demographic collapse caused by smallpox. Tsleil-Waututh people selected fifteen distinctive geological features along the shoreline of Indian Arm for marking. It is suggested that these locations were highly significant places to past Tsleil-Waututh people because they were physical embodiments of oral traditions (sxwoxwyiam) and associated with underwater-dwelling supernatural creatures (stl’aleqem). Relying on local oral traditions, regional archaeology, and local ethnographies, the article argues that these specific locations had very ancient roots in Tsleil-Waututh history but were marked in the early contact period with red paint by Tsleil-Waututh ritualists (shxwla:m, “Indian Doctor”). They did this to connect with supernatural powers in these locations, to preserve oral histories associated with them, and thus to contribute to the demographic revitalization of the Tsleil-Waututh people. The article contends that Tsleil-Waututh rock painting is not an essentialized cultural practice but a historically contingent one—a reflection of specific events.

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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.870
Threshold uncertainty score0.259

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 studies0.0060.008
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.038
GPT teacher head0.383
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

Citations5
Published2018
Admission routes1
Has abstractyes

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