A framework for understanding land control transfer in agricultural commodity frontiers
Bibliographic record
Abstract
Abstract Across the globe, the expansion of large‐scale commodity agriculture is occurring not into empty space but over existing social systems. An understanding of the dynamics of expansion and associated impacts of commodity agriculture thus fundamentally requires examining how existing control regimes are dissolved and, simultaneously, how novel ones are assembled in order to make way for the changes in resources use that characterize these transitional moments. With this in mind, in this article, I provide a broad review of the strategies used to secure control over land prospected for agricultural commodity production, distinguishing between the tactics that are applied by agro‐interested actors in order to ‘break down’ forms of existing land control, those they apply in parallel to ‘build up’ new control structures, and those strategies that are applied by actors (often smallholders) wishing to ‘hold on to’ the control that they have. I then present a framework for examining the dynamics of control transfer that builds on this analytical structure of ‘breaking down’, ‘building up’, and ‘holding on to’ control.
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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.042 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".