Climbing the Trail to Heaven: Traditional Funerals and Burial Practices in Dane-Zaa Territory-An Ethnographic Account from Northeastern British Columbia
Bibliographic record
Abstract
The purpose of this research is to investigate two customary funerals conducted by the Dane-zaa First Nation of Northeastern British Columbia, known as the Doig River First Nation. Both funerals included a lot of drumming, singing, and dancing around the fire in keeping with the Dane-zaa custom. Still, there was one key distinction between the two rituals. The funeral held in 2019 for Janice Askoty was a hybrid service that included a Christian liturgy and customary rituals. Such a ritual highlighted the conflicts that already existed among community members over faith and belief systems. There were no conflicts throughout the Christian service that was part of Annie Oker's 2020 funeral. In this paper, the researcher use the notion of syncretism and my observations to illustrate how Christian practices have been merged with indigenous cultural practices, symbols, and beliefs to create new blended practices. Simultaneously, the researcher highlight how certain customs (such as drumming, singing, and dancing around the fire) have endured to this day because they have not been altered by outside forces. Finally, the researcher discuss how the history of colonialism continues to show itself in funerary celebrations and how the community members view, confront, and resist it.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.021 | 0.008 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".