Vanishing the Haida: George Dawson's ethnographic vision and the making of settler space on the Queen Charlotte Islands in the late nineteenth century
Bibliographic record
Abstract
Recent geographical studies of colonialism in British Columbia have illuminated the ways in which both imperial and native spaces came to be constructed in the province during the eighteenth and nineteenth centuries. Less attention has been paid to the discourses and practices inherent to making settler space in late nineteenth century British Columbia. This article focuses on geologist George Dawson's 1880 report on the Queen Charlotte Islands in order to analyze how his imaginative geography of future settlement and resource extraction (Dawson's principal contribution to the making of settler space on these islands) was legitimized by the past‐oriented and quite nostalgic ethnographic study of the archipelago's indigenous Haida population included in the report's appendices. In essence, the ethnographic appendix articulated a colonial narrative of Haida decline that justified their virtual erasure from the descriptive and cartographic depictions of the islands' future resource landscapes set out in the main body of the report. By depicting the Haida as another example of North America's ‘Vanishing Indian’, Dawson's report served to position an ‘authentic’ Haida society in a rapidly‐vanishing past from which they could stake few viable claims to the highly‐coveted resource landscapes of the Queen Charlotte Islands.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.028 | 0.025 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".