Transforming the Work of Geographical Indications to Decolonize Racialized Labor and Support Agroecology
Bibliographic record
Abstract
Critical scholarship on geographical indications (GIs) has increasingly focused upon their role in fostering development in the Global South. Recent work has drawn welcome attention to issues of governance and sparked new debates about the role of the state in GI regulation. We argue that this new emphasis needs to be coupled with a greater focus upon local social relations of power and interlinked issues of social justice. Rather than see GI regimes as apolitical technical administrative frameworks, we argue that they govern emerging public goods that should be forged to redress extant forms of social inequality and foster the inclusion of marginalized actors in commodity value chains. In many areas of the world, this will entail close attention to the historical specificities of colonial labor relations and their neocolonial legacies, which have entrenched conditions of racialized and gendered dispossession, particularly in plantation economies. Using examples from South Africa and South Asia, we illustrate how GIs conventionally reify territories in a fashion that obscures and/or naturalizes exploitative conditions of labor and unequal access to land based resources, which are legacies of historical disenfranchisement. Like other forms of neoliberal governmentality that support private governance for public ends, however, GIs might be shaped to support new forms of social justice. We show how issues of labor and place-based livelihoods increasingly influence new policy directions within Fair Trade agendas while concerns with “decolonizing” agricultural governance now animate certification initiatives emerging from new social movements. Both initiatives provide models for shaping the governance and regulation of GIs in projects of rural territorial development that encompass principles of rights-based development to further social movements for rural social justice.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".