The sea, the ship, and I : stories, things and objects from oceanography during the Cold War
Bibliographic record
Abstract
This dissertation examines how and why men on oceanographic research vessels in the middle of the 20th century used storytelling as part of scientific practice. I weave scholarship on literature and science together with the history of oceanography and demonstrate that oceanographers constructed their social world through narration. To begin, I look closely at a diary, memorandum, cartoon, and motion picture and then illuminate how the process of creating these narratives formulated collaboration, persuasive strategy, friendship, and community. Each author used the process of narration to make sense of expedition life and determine how best to proceed as a member of the oceanographic community. I argue that storytelling was not merely a pastime: it formed an integral part of social functioning of science at sea. Inspired by scholarship concerned with things and objects, the study also uses the content of the stories to investigate the ways in which things and objects at sea did four actions: influenced the oceanographic gaze on the Pacific, altered the patronage relationship between oceanography and the U.S. Navy, facilitated the construction of a shipboard ecology built upon collaboration, and came to represent Scripps as the dominant creator of knowledge in the Pacific. While historians have explained how elite actors created the geopolitical arrangements that determined ocean science in this period, this project argues that non-elite scientists, graduate students, Navy crew, and medical doctors recorded everyday experiences on expeditions in stories because their contributions to shipboard life and work were also a crucial component of the development of oceanography at sea during the Cold War.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.024 | 0.035 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".