Agricultural Resources, Agricultural Production and Settlement at Confederation
Bibliographic record
Abstract
IN EASTERN CANADA THE AGRICULTURAL LANDS were largely settled by the time of Confederation, although on many farms much soil still lay under forest. 1 Most families gained a livelihood by farming, but in the earliest days of creating a farm from the wilderness many also worked for wages, perhaps on others' lands, perhaps in lumber camps or the fishery. Once sufficient acreage was cleared, the land supplied a large portion of a family's needs; meat, milk, butter, vegetables and cloth were all produced on the farm.2 Other farm products required local processing before they were useful; wheat needed to be ground to flour and oats to meal, logs provided better housing when sawn into boards, hides were tanned to leather and manufactured into harnesses or shoes by skilled artisans, wool was carded and home spun cloth was fulled, and for some the enjoyment of rye and barley was much increased by distillation or brewing. As a result, agricultural communities always enjoyed a degree of diversification, since farming families' willingness to exchange farm produce for processed goods gave artisans a livelihood. Even with local manufacturing, neither the farms nor the cluster of activities in farming communities could meet all the needs and wants of settlers. Sugar, tea, coffee, fine cloth, quality shoes and boots added greatly to settlers' comforts, while tools, nails and other iron goods helped farmers become more efficient in their trade.3 To secure these imported commodities, external markets for some local produce had to
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.013 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.001 |
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".