Bibliographic record
Abstract
The People on the Land During the last sixteen weeks, much of our discussion about the problems before us in the post-war period has focussed on urban life.When we talked about full employment, we considered mainly our industrial set-up.When we examined the state of affairs in our own community, it was usually a city or a small town.Tonight our attention turns to the people on the land.Many of us who live in Canadian cities or small towns were brought up on a farm.But whether or not we have a personal link with the farming industry, what happens to it is of vital importance to the well-being of Canada as a whole, for almost a third of the Canadian people live on farms.Farming is the second most impor- tant occupation in our country.In 1935 the value of farm products comprised 26% of the total value of production, with manufactur- ing alone ranking higher.This enterprise supplies almost all the food Canadians eat (with the exception of a few products not grown here, such as coffee, and some items which add to the variety or quantity of the home supply, such as fruits).It supplies raw material for about 36% of Canada's manufacturing enterprises.In 1928 goods of farm origin actually accounted for more than half (on a value basis) of all Canadian exports.In 1930 it was estimated that "practically half the domestic market for the products of urban manufacture is provided by Canadian agriculture."(Economic Organization of Canadian Agriculture, by J. F. Booth).This means that Canadian industry loses an important market when Canadian farmers can't afford to buy its products.If Canadian agriculture is not prosperous, the entire population of our country suffers. CRISIS ON THE FARMCanadian farmers, like the rest of us, are worried about the future because of the past.Canadian farming has been in a state of crisis since the 20's.Farmers were the first to experience the disastrous effects of falling prices ; their returns decreased sharply in the post-war depression between 1921 and 1923.Farm prices failed to rally to the same extent as profits or even wages.They declined abysmally during the great depression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.121 | 0.032 |
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".