Can or did domestication occur without regular tillage?
Bibliographic record
Abstract
A recent paper by Weide et al. 1 argues that cereal domestication in Southwestern Asia occurred without regular recourse to tillage and sowing.Their proposed model goes against a long tradition of thought which places cultivation, which for cereals traditionally involves annual cycles of tillage, sowing and harvesting 2,3 , at the heart of domestication, a process referred to as "pre-domestication cultivation" 4 .Weide et al. 1 apply FIBS (Functional Interpretative Botanical Systems) analysis to modern and archaeobotanical datasets, comprising charred cereal remains and weed seeds.Contrary to previous FIBS studies using multiple functional traits, the authors rely on just flowering duration, and to a lesser extent vegetative reproduction.These traits are used to define disturbed "arable" and undisturbed "non-arable" environments, inferred from modern surveys of arable fields and wild cereal grasslands, respectively.Archaeobotanical samples were assigned as "arable" or "non-arable" using these two traits, by comparison with modern environments, through discriminate analysis.Two early pre-domestication cultivation sites in Syria, Jerf el Ahmar and Dja'de aligned more closely with "non-arable" grasslands than to modern "arable" fields.This observation led Weide et al. 1 to suggest a new model of "pre-domestication cultivation" (PDC) without regular tillage and annual sowing.They then see their revised PDC model, incorporating lower selection pressures, as underpinning protracted domestication, spanning millennia.
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 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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".