A German on the Prairies: Max Sering and settler colonialism in Canada
Bibliographic record
Abstract
In 1883, the Prussian Government sent the young agrarian economist, Max Sering, on a six month fact-finding tour of North America in order to a) discover why grain was being produced so much more cheaply there and b) why so many Germans were fleeing perfectly good soil in East Central Europe to settle on similar land in Nebraska and Manitoba. On this tour, and most importantly while in Manitoba, Sering discovered an organized program of ‘inner colonization’: the government was bringing citizens from the ‘full’ East (Ontario) and providing them land in the ‘empty’ West, ‘civilizing’ through farming Natives already in the West, securing the national border to the south, and creating strong, healthy, fertile, and conservative sons and daughters for the future of the nation. This is the concept that Sering brought back to Germany and in 1886 Chancellor Bismarck began a ‘Program of Inner Colonization’ in Germany's ‘East’ that began as something akin to what was taking place in the Canadian Prairies, but over the following decades evolved into something Sering could never have imagined.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.046 | 0.017 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".