Bibliographic record
Abstract
INTRODUCTION This chapter covers growth and structural change in Canada over the last century. During this period Canada grew from a country with a small and widely scattered population and vast unsettled lands to an urban-industrial nation. The transformation, although not without its problems, nevertheless was highly successful, chiefly due to the discovery and then successful exploitation of a series of staple exports, beginning with wheat in the 1890s and broadening to include pulp and paper, minerals, and, most recently, oil and natural gas. The export of natural resources is therefore an enduring theme in any explanation of the forces generating long-run growth in Canada. However, as the century progressed, other factors were added to the determinants of growth. With a larger population and higher average income the Canadian economy itself proved to be an effective promoter of growth. Hence, by the end of the century, the forces generating change had become more complex. They involved influences associated with both the international sector as well as with internal developments, and their interaction. What follows, then, is an attempt to offer explanations for these changes and to set out some of their consequences. The twentieth century can be divided into three broad periods. First, the years from 1896 to 1929 were ones of rapid growth. They include such important developments as western settlement, the emergence of wheat as Canada’s primary export staple, and the creation of an integrated national economy. Second, the period 1930 to 1950 is one of disruption. It covers the Great Depression and war.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".