Extraction and the Ocean “Frontier”: Dispossession, Exclusion, and Resistance in Namibia
Bibliographic record
Abstract
Abstract The perceived neglect of the ocean to state and industry actors has seen frontier rhetoric emerge as it is rendered visible under the Blue Economy agenda. By framing the marine scape as underutilised, capitalist expansion is being legitimised. Drawing on the case of Namibia, I argue that the afterlives of colonialism and apartheid are being repurposed to present the ocean as a Blue Economy opportunity. The physical disconnection of citizens from the marine scape, and the dominance of fishing and mining industries, has been used by state and development actors to present it as empty of socio‐cultural relations. However, to declare Namibia’s coasts and ocean as forgotten unless articulated through capital is to conceal that they have been labelled “no‐go” zones. I argue that, by considering exclusions and looking beyond proximity in discussions of equity and representation, the marine scape is articulated by civil society, to elucidate forms of resistance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.014 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".