Territoriality and the Technics of Drylands Science in Palestine and North America
Bibliographic record
Abstract
At the turn of the 20th century, agricultural experts in several countries assembled a new agro-scientific field: dryland farming. Their agricultural research practices concomitantly fashioned a new agro-ecological zone—the drylands—as the site of agronomic intervention. As part of this effort, American scientists worked in concert with colleagues in the emerging Zionist movement to investigate agricultural practices and crops in Palestine and neighboring regions, where nonirrigated or rainfed agriculture had long been practiced. In my larger manuscript project, I consider how the reorganization of rainfed farming as dryfarming is central to the history of both the Middle East and North America, where it was closely related to modern forms of power, sovereignty, and territoriality. I suggest that American interest in dryfarming science emerged out of a practical need to propel and sustain colonization of the Great Plains, but later became a joint effort of researchers from several emerging settler enterprises, including Australia, Canada, and the Zionist movement. In contrast to a naturally ocurring bioregion, I argue that the drylands spatiality was engineered through, rather than outside, the territorialization of modern power.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.031 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".