Bibliographic record
Abstract
Abstract This article lays the groundwork for a Marxist theory of the international law of land-grabbing. It argues that any comprehensive politico-economic analysis of land-grabbing must also be a politico-economic analysis of the law of land-grabbing. It argues further that Marx’s account of ‘primitive accumulation’ in Capital – an account it presents as an historical explanation of the transition to capitalism as well as a general theory of ‘extra-economic’ force deployed through state power, including, crucially, the power of law – is helpful for developing an analytical framework for understanding the legal facets of land-grabbing. Political economists, rural sociologists, and social and political theorists have argued for and against the applicability of Marx’s theory of ‘primitive accumulation’ to the contemporary wave of global land grabbing. Intriguingly, though, no international lawyers have grappled with the question of whether a specifically Marxist approach to the phenomenon can or should be developed. This article does so, contending that contemporary land-grabbing is unintelligible absent a theory of capitalism, and that the processes whereby capitalism transforms land and labour are unintelligible absent a theory of the periodic waves of legally mediated ‘primitive accumulation’ that propel it forward. The article pays particular attention to the work produced by Olivier De Schutter during his tenure as United Nations Special Rapporteur on the Right to Food.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.026 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".