Agroforestry Nomenclature, Concepts, and Practices
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Agroforestry in the United States and Canada is driven by sustainable development and growth in the “green” marketplace, which in turn will positively affect rural decline and the environmental impacts of agriculture. Agroforestry practices bridge the gap between production agriculture and natural resource management. Four key criteria characterize agroforestry practices in the United States and Canada and distinguish them from other practices. To be called agroforestry, a land use practice must satisfy all of the following four criteria: intentional, intensive, integrated, and interactive. Five categories of agroforestry practices that embody these criteria are recognized in the United States and Canada by the Association for Temperate Agroforestry. These practices include: riparian and upland buffers, windbreaks, alley cropping, silvopasture, and forest farming. Finally, one must recognize that there are two distinct perspectives on agroforestry in the United States and Canada, and it is important to distinguish them from a nomenclature standpoint.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it