Immediate Backgrounds of the Present Agricultural Policies and Programs
Bibliographic record
Abstract
Excerpt: The past decade has witnessed the development of agricultural plans on an unprecedented scale throughout the world. The ultimate development has probably taken place in the totalitarian countries such as Germany, Italy, and Russia. In Germany, for example, the farmer now tills the soil as a public servant for the benefit of the State. The democracies have reached no such situation but even there the growth of controls has been marked. The United States, Canada, Great Britain, Australia, and France have all experimented with various schemes, and the list of countries could be extended almost indefinitely. Previously the policies relating to agriculture had been relatively simple, public education, research dissemination of information and so on. The difficulties induced by the collapse after the war led to the attempt to bolster the position of the agricultural group throughout most of the world. One may suspect that we have come close to the first era in this country in the series of experiments, but it is too early to know whether we have learned much from these experiences or not. It is, however, certain that we are nowhere near the end of our difficulties; Indeed, one may easily imagine that we are simply in the lull before the storm, and that the not too distant future promises difficulties of even greater magnitude than those through which we have just passed.
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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 | 0.002 | 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 | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.084 | 0.012 |
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".