Thinking from multiple oceans: historical and elemental lineages and futures of ocean geography(s)
Bibliographic record
Abstract
This article considers how a tension in critical ocean geography between thinking with and thinking from the ocean can be elucidated through an engagement with a number of Black scholars asking related questions. Focusing on Herman Melville’s Moby-Dick and its interpretation by C.L.R. James and Paul Gilroy, as well as other scholars in the critical ocean geography/critical ocean studies and Black studies traditions, I suggest that a pervasive challenge to oceanic thinking is the need to balance, on the one hand, the tendency to think with the ocean’s perceived exceptionality as a scaffold for non-normative thinking with, on the other hand, the desire to think from the encounters that occur in ocean-space and that historically have played a crucial role in constructing identities and futures of peoples who bear the experience of the ocean’s watery depths and turbulence. I conclude by arguing for an approach that is both historical and elemental, in order to construct narratives that point to the ocean not simply as a repository of meaning or as a site for projecting dreams, but as a lively space where thoughts, understandings, and narrations emerge from the entanglements of water and life, forcings and histories, memories and forgettings, that occur within.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.054 |
| Scholarly communication | 0.011 | 0.017 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".