Bibliographic record
Abstract
Abstract Indigenous oral histories on the Pacific Northwest Coast have been woven into archaeological narratives for generations. Yet, what is often left unaddressed are the ways Indigenous oral histories and archaeological science converge and diverge when recounting histories. This chapter discusses braiding these two knowledge systems by examining the history of La̱xg̱a̱lts’ap, a sacred watershed for the Gitga’at First Nation and the setting of foundational oral histories of Gitḵ’a’ata culture. Through a multidisciplinary collaboration, the first author, Gitḵ’a’ata anthropologist Spencer Greening, and his two archaeological colleagues, Dr. Dana Lepofsky and Dr. Bryn Letham, share their journey of hunting for archaeological village sites with oral traditions at the helm. Their exploration follows an ancient migration into La̱xg̱a̱lts’ap after a time of immense ecological change in Gitḵ’a’ata interior homelands. The oral narratives are rich in details about political nuance and relationships with neighbors, landscapes, and spiritual beings. The archaeological component of the study complements this knowledge by documenting how the migration is nestled within at least 10,600 years of human occupancy in the watershed, and paleoenvironmental work documents significant changes in sea level since deglaciation of the watershed over 14,500 years ago. A deep-time narrative is navigated and teased apart, which is sometimes difficult to bound within Western temporal or spatial terms, while grappling with how a complex geomorphic context influences an understanding of past lives. Despite the nuances, or perhaps because of them, the discourse adds to an understanding of the deeply rich and complex Gitḵ’a’ata past in the La̱xg̱a̱lts’ap watershed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.046 | 0.005 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".