Uneven decommodification geographies: Exploring variation across the centre and periphery
Bibliographic record
Abstract
The Covid-19 pandemic has revealed significant variation in the scale and form of decommodification across the capitalist world economy. To explore these uneven decommodification geographies this article develops a new conceptual framework that combines a critical Polanyian reading of decommodification with Latin American insights into centre-periphery structures and relations. The decommodification of land and labour in Britain (centre) and Ecuador (periphery) are then analysed from this conceptual perspective. The comparative analysis reveals significant variation in the scale and form of decommodification between the two countries during the pandemic. However, some important similarities are also observed, especially in relation to the (de) commodification of land. Here, the article draws on the corporate food regime literature to better understand similarities and differences between Britain and Ecuador. By revealing the uneven and shifting terrain of decommodification, this article makes a novel contribution to wider debates about the capitalist conjuncture and the intensifying crises of neoliberal capitalism.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".