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Record W4240586064 · doi:10.24124/2017/58909

Raven bloodlines, Tsimshian identity: An autoethnographic account of Tsimshian Wil'naat'al, politics, pedagogy, and law

2017· dissertation· en· W4240586064 on OpenAlexaff
Spencer Greening

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicAnthropological Studies and Insights
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsIdentity (music)IndigenousEthnographyPoliticsGender studiesSociologyPerspective (graphical)AnthropologyPolitical scienceLawAesthetics

Abstract

fetched live from OpenAlex

Raven Bloodlines, Tsimshian Identity is an ethnographic discussion on the sociopolitical values lived by the Tsimshian. This thesis is written from my own Tsimshian perspective, describing my pedagogical journey of Tsimshian identity, politics, and law in a matrilineal society. This thesis aims to recognize the inclusiveness and importance of matrilineal ties between intertribal communities, and highlight how western interpretations of anthropological literature have led to colonial influence in areas such as individualized rights, responsibilities, and land ownership amongst the Tsimshian. I interviewed the Tsimshian Hereditary Chiefs of my phratry to gain insight into the responsibility held to one’s family, community, and nation. By understanding and living ancestral sociopolitical values, my work aims to add to the discussion of Indigenous methods, ethnography, and pedagogy, while helping the reader gain insight into Tsimshian sociopolitical structure and its influence on intertribal relationships.

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 score0.975
Threshold uncertainty score0.050

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 studies0.0130.013
Scholarly communication0.0030.004
Open science0.0000.002
Research integrity0.0010.002
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 head0.052
GPT teacher head0.428
Teacher spread0.375 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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