‘The last frontier’: rationalizing the spread of farming into the boreal woods of Canada, <i>c</i>. 1910–1940
Bibliographic record
Abstract
As the twentieth century opened, there were rumours that the cheap land underpinning the dramatic spread of settlement in the previous century might be running out. There were strong motivations, generated particularly by the large body of land seekers with a passion for farming, to hold off the demise of the famous agricultural frontier. Also wedded to the continuation of a frontier were politicians and civil servants across the country. Whether it was a subconscious expectation that the frontier would simply continue or a fear that its disappearance would lead to unpredictable social disturbance, politicians encouraged expansion beyond what was known to be good farmland. The major source of new land, from c. 1910, was the boreal forest. There was a steady accumulation of information about the North that was readily available to government officials but only indirectly to ordinary land seekers. Although the news about farming conditions in the boreal margin was unpromising except for a few pockets, independent and assisted farm settlements continued into the 1930s. The typical two‐thirds of farm failure within one generation in most of the new boreal settlements caused a great deal of settler grief and forced reluctant officials to respond to the negative scientific evidence and to reassess frontier nostalgia. The Second World War provided both a denouement of the northern farm settlement and a reason for many people to depart the ‘last frontier’.
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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 | 0.001 |
| Science and technology studies | 0.023 | 0.029 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".