The sociology of agriculture in transition: The political economy of agriculture after biotechnology
Bibliographic record
Abstract
In 2007, a global food crisis brought the topic of agriculture back into the public eye, and retriggered debates about the ability of agricultural industrialization to feed the world. As a nature-based process and an exception to capitalist industrialization, agriculture trends are difficult to assess. One of the more productive attempts to do so has developed conceptual tools that account for the distinction from typical capital accumulation patterns, notably Goodman, Sorj, and Wilkinson’s (1987) classic concepts of “appropriationism” and “substitutionism.” Agricultural biotechnologies are testing the limits of even these more refined conceptualizations, as the technologies’ associated proprietary framework — including seed saving restrictions, grower contracts, and patent infringement litigation — is reorganizing many traditional agricultural practices. Drawing on case studies in Mississippi, U.S. and Saskatchewan, Canada, this paper argues that these trends suggest a need for a new concept in political economy of agriculture theory, which I term “expropriationism.” This concept identifies several aspects of an agricultural reorganization premised on legal means to enhance capital accumulation and on separating corporate ownership from liability. This accumulation strategy has important implications given the high salience that agriculture has for society.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.031 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".