Bibliographic record
Abstract
There is no More Sea Power. What Kind of Awe can a Fleet or an Aircraft Carrier inspire in the Nuclear Age, Whose Blasts have given a new character to military majesty and sublimity and whose marine vehicles are hidden beneath the waves? Nor do the ocean-girding voyages of global commerce offer a sense of majesty, the neat stacks of containers rising high above the decks being mere floating versions of the endless stacks at the prosaic, crane-filled ports of Busan, Long Beach, Elizabeth, or Singapore. The sea is full of transport, labor, and industry, but spectacle has moved elsewhere: what remains of the nautical in the visual media is the nostalgic sublimity of sinking ships or historical reenactments of blue-water glory. As if to underscore this vacuum of hegemonic maritime power in an age of shock and awe, the pirates of Puntland and Sulu still have their way in the Gulf of Aden and the Strait of Malacca, as they have for centuries. Latter-day posturing by the epigones of interstate maritime power contenders approaches farce, as in the struggle for the Arctic, joined by Russia, Canada, the United States, Denmark, and Norway, punctuated by Russian flags at the bottom of the sea and by the specter of Danish military incursion into what Canada claims as its sovereign territory (Craciun).
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.190 | 0.092 |
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".