Bibliographic record
Abstract
Summary This article reimagines scuba diving as a form of ethnographic immersion that allows humans to experience life on earth from an underwater perspective. I argue that scuba divers are both posthuman in their cyborgian transcendence of the basic limitations of our species and prehuman in their metaphorical regression into womb‐like oceans, from which all life on earth evolved. I conceptualize divers as (p)reborn humans. Underwater, symbolic modes of human communication devolve to iconic and indexical forms of gesturing that are more in tune with surrounding ecosystems. Scuba diving involves shamanic navigation between lifeworlds, processes that are deeply ritualistic and psychoanalytically significant. Through first‐hand narrative accounts, divers bring new forms of relational knowledge into the public sphere. Bearing in mind the politics of being underwater, I contend that scuba diving can foster a change in how humans apprehend the ocean, from top‐down representation to bottom‐up lived experience. Scuba diving reshapes attention in ways that could inspire collective appreciation for the blue planet that sustains us. Against the backdrop of global environmental change, I call for a shift in the way that humans see and think about the ocean, from above water to below.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.025 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".