Trawling the Ocean of Grass: Soil Nitrogen in Saskatchewan Agriculture, 1916–2001
Bibliographic record
Abstract
Abstract Using a socioecological metabolism approach to analyze data from the Census of Agriculture, this article examines the underlying soil fertility of two case study areas in the Canadian province of Saskatchewan through the calculation of soil nitrogen balances. The Rural Municipalities of Wise Creek and Livingston are 300 miles apart and therefore have different topography, soil types, and rainfall levels, even though both are within the northern Great Plains. Over 85 years, from first settlement in the 1910s until the beginning of the twenty-first century, Wise Creek agriculture focused increasingly on livestock production while in Livingston farmers began to grow a greater variety of crops, most notably incorporating canola into rotations. Despite the differences between the two case studies, the pattern of soil nitrogen losses was remarkably similar, with biomass yields declining along with soil nitrogen. The addition of chemical nitrogen fertilizers since the 1960s did not produce yields matching historic highs, nor did a renewed focus on livestock. Wise Creek and Livingston showed two different responses to declining yields, but neither one ultimately provided a long-term solution to the problem of soil nutrient depletion and consequent productivity declines.
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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 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".