Conversion versus Ethnography: Adrien Gabriel Morice and the Western Dene
Bibliographic record
Abstract
Conversion versus ethnography—how can one be both a missionary and an ethnographer? Is there not an inherent contradiction between trying to radically change a culture and society through religious conversion, while simultaneously trying to “scientifically” record the same culture and society? Yet, many missionaries found themselves in the situation of attempting to preserve via their academic writings the very cultures and societies they condemned and sought to change in their religious career. This article is about one such missionary, Adrien Gabriel Morice, Oblate missionary to the Tsilhqot’in (Chilcotin), Dakelh (Carrier) and Tse Keh Nay (Sekani) of northern central British Columbia. It examines how he dealt with this inherent contradiction and concludes that not only did it hinder his conversion of First Nations, but also prevented him from making the academic move from Enlightenment ethnology to social Darwinism and Boasian anthropology. Nevertheless, despite the fact that this inherent contradiction cost him his mission post at Stuart Lake in 1903, Morice benefitted from his first-hand experience at that post and became influential as an ethnographer with regards to Dakelh social organization, religion, burial practices and gender. In this achievement, he was able to leave a lasting legacy despite the inherent contradiction between his role as a missionary and as an ethnographer.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.032 | 0.037 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| 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".