Bibliographic record
Abstract
migrants from Europe and their offspring, competing against the indigenous people and eventually replacing them. But those waves were backed up by the power of the American and Canadian nation states, with their well-armed military, their well funded railroads, and other technology and capital. Science too was initially on the side of the invaders. But after World War One that frontier began to run out of free, abundant land. Then began what I will call a “post-frontier” science, especially ecological in content, that represented a very different attitude toward the white man’s conquest. Scientists like Frederick Clements, John C. Weaver, Paul Sears, and Stan Rowe, all natives to the Great Plains, laid the foundations for what is now a powerful critique of frontier agriculture. My contribution to the panel will summarize that critique briefly but focus mainly on the more recent work of Wes Jackson, founder and longtime president of the Land Institute. He has strongly criticized the frontier ethos for its the lack of understanding of the native ecology of the grasslands. In its place he has offered a vision of “perennial polyculture,” using nature as a model for agriculture in an era of limits. That model has not only been making a growing impact on American thinking but has now spread to other continents. Will the end of this frontier cycle and scientific reappraisal turn out to be what Jackson calls a “new agriculture,” one based on learning from the past and one that can change farming all over the world?
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".