Assessing agricultural adaptation to changing climatic conditions during the English agricultural revolution (1645–1740)
Why this work is in the frame
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Bibliographic record
Abstract
Abstract This article examines the impact of climatic variability on the English Agricultural Revolution using Allen’s Nitrogen Hypothesis. While half of the variation in yields can be attributed to nitrogen-fixing plants, better cultivation, and improved seeds, the remainder can be attributed to changing climatic conditions during the relatively cold period from c. 1645–1715 and the subsequent warmer phase. The study finds that farmers made even greater efforts than observed yields during the colder and more humid climate of the second half of the seventeenth century and the early eighteenth. Conversely, increasing temperatures in the following period had a positive effect on agricultural productivity, indicating that farmers' role during this phase have been overrated.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.012 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it