The Eagle Said, “I will Take You Home Again”: Reclaiming Indigenous Histories from the Geological Survey of Canada, c. 1870–1910
Bibliographic record
Abstract
Raymond Miron (Anishinaabe and French, Bawaating/Sault Ste. Marie, Ontario) and Robert Nolan (Anishinaabe, Batchewana First Nation, Ketegaunseebee/Garden River, Ontario) worked with the Geological Survey of Canada (GSC) in the late nineteenth and early twentieth centuries, specifically with one of its employees, Robert Bell, a settler of Scottish descent. Miron and Nolan were two of the many Indigenous Peoples who shared their expertise, knowledge, skills, technologies, maps, and travel routes with Bell as he endeavoured to explore the northern half of North America for the GSC. However, in his published reports, Bell evaded acknowledgment of the many contributions made by Indigenous Peoples, despite the dependency of his work upon them. Nevertheless, by attending to silences in colonial archives and reading between the lines of the GSC’s sources, Indigenous stories can be uncovered and reclaimed from the narratives constructed by White explorers. What Miron, Nolan, and so many other Indigenous people shared with Bell, as well as what he took from them without consent, was based on rich geographic and geological knowledge that predated the GSC by thousands of years. Indeed, the significance and brilliance of Indigenous knowledge permeates the records of the Geological Survey, including those written by Bell, and defied colonial attempts to erase or deny it.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.026 | 0.012 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".