Accumulation by Dispossession or Accumulation without Dispossession: The Case of Contract Farming in India
Bibliographic record
Abstract
According to David Harvey, Accumulation by Dispossession (ABD) has become the dominant form of accumulation under the mantra of neoliberalism backed by the State policies, whether in developed or in developing economies. Using empirical evidence on contract farming in India, I argue that capitalist accumulation can indeed occur without dispossession. I show how a class of petty capitalist farmers (petty, in comparison to corporate capital) is encouraged to maintain its private property (land) and to enter into commercial contracts with big industrial (multinational) companies to deliver certain farm products at a pre-determined price. These companies have no intention to dispossess the farmers, and they do not have to. As a structure of multiple class actors (big business; capitalist farmers; rural labour), contract farming is a process that represents centralisation (and concentration) of capital and points to the ways in which agrarian and industrial capitals are intertwined. Contract farming as a form of accumulation is based on appalling working conditions of labour, including vulnerable women workers and migrants, on contract farms, and it exhibits much geographical variation in its occurrence.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.018 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".