Charted waters? Tracking the production of conservation territories on the high seas
Bibliographic record
Abstract
Abstract Marine protected areas (MPAs), a common marine conservation tool, function as both objects of governance and as a form of territory. This article tracks the long‐term effort to produce conservation territories on the high seas, in areas beyond national jurisdiction. Drawing on data collected at five international environmental meetings, the paper demonstrates how an imaginative geography of the high seas is being simultaneously constituted by scientific and technological advances, particularly geospatial visualisations, as well as coordinated efforts to advocate for and develop a new international conservation instrument (an implementing agreement under the United Nations Convention on the Law of the Sea). Conventional understandings of territory constrain this effort by equating territory with the state. At the same time, the case of high seas conservation contributes to critiques of this conceptualisation of territory, by showcasing the role of multiple actors in seeing and controlling ocean space. Overall, the production of territory on the high seas both reflects and informs a shift in the “frontier mentality” of the oceans, as conservation and science frontier as well as economic frontier. Diverse responses to representations of, and policies for, the high seas point to both possibilities and limits of territorial thinking in the oceans.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".