The continuity of settler colonial narratives: the diary of a nineteenth-century dominion land surveyor and the enduring language of harm
Bibliographic record
Abstract
This article analyzes the writings of a prominent Canadian nineteenth-century land surveyor and scientist to show the continuity of settler colonial narratives from his time until ours. As a Dominion Lands Surveyor, Otto Julius Klotz (1851–1923) was part of the vanguard of his white-supremacist, expansionistic, industrializing society; a group of front-line invaders who facilitated the taking of land from Indigenous people and nations, and transferred it to mostly white men. Employing a biographical microhistorical approach to settler colonialism, this research examines Klotz’s personal diary and the events contained in it. Klotz was able to live the ideals of heteropatriarchal white masculinity and middle-class respectability, and his voluminous, life-long diary demonstrates the ways in which his privilege was actively advanced by dehumanizing others. I show the ways this land surveyor mourned the world he was destroying at the same time as he celebrated the world he was bringing into being, and how this apparent contradiction is central to settler colonialism and anti-Indigenous racism, and is still with us today. I argue that understanding the continuity of settler colonial narratives can help us to better understand our world while we strive to construct decolonial narratives and find ways to reconnect to one another and the land.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.034 | 0.030 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.003 | 0.007 |
| 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".