The Sea Unites Us but It Is Governed to Keep Us Apart: Restoring the Creole Afro-Indigenous Sea Mobilities in the Southwestern Caribbean.
Bibliographic record
Abstract
Increasingly, marine governance advocates for ocean justice and, within it, the rights of coastal communities and indigenous people over the ocean space. Yet, international and state sea regimes strengthen border restrictions, impeding people’s mobilities and fracturing the sea interconnectedness. Against this backdrop and delving into the empirical data gathered through ethnographical research, the paper examines the intangible and the material sea (im)mobilities experienced by the Creole Afro-Indigenous communities in the Corn Islands and the San Andres Archipelago in the Southwestern Caribbean Sea. Through the lens of critical ocean geography and mobility studies, it reveals how the maritime boundary regimes and the frameworks of oceans territoriality have impacted indigenous island spatialities in the Nicaraguan-Colombian marine border area for the last decades, disrupting family and social connections, weakening the communities’ autonomy, and impeding food and provisions supply between the islands, thus threatening the indigenous rights with implications for ocean justice. The paper finally considers Creole Afro-Indigenous maritime activism’s prominent role in decolonizing marine governance in the Greater Caribbean region, suggesting the relevance of laws, norms, structures and ocean governance institutions to acknowledge and incorporate these alternative legalities.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".