Fish Encounters: Aquariums and Their Veterinarians on a Rapidly Changing Planet
Bibliographic record
Abstract
The extensive body of social science and humanities scholarship on zoos rarely discusses aquariums. Despite their independent historical trajectory and unique characteristics and challenges, aquariums are typically considered the younger sister to the more established terrestrial zoo institutions. This article is an initial exploration of modern public aquariums through the eyes of these institutions’ veterinarians, a small but rapidly growing, and quite influential, professional cohort. Drawing on in-depth interviews with a handful of aquarium veterinarians in various sites — including the United States, Canada, Israel, Portugal, Denmark, and Germany — the article documents some of the everyday challenges that these medical practitioners face when attempting to manage the health and wellbeing of captive marine animals. Their feet in several worlds, aquarium veterinarians must balance their medical training and animal welfare sensibilities with the specific nature of the aquatic animals under their care, and also with the understanding of their evolving responsibilities toward ocean conservation. For these professionals, the rights-welfare-conservation approaches to animal care are not abstract ideas but rather real-life situations that dictate their actual modes of practice in caring for marine animals. This can only be an initial study and thus highlights the need for additional scholarly work in the social sciences and humanities on aquariums, their wet forms of life, and the challenges — as well as the opportunities — that their management poses to the human caretakers of this space. This scholarly need is especially acute in light of the declining state of extant species and ecosystems in the world’s seas. Public aquariums and their veterinarians will arguably perform increasingly important roles in the conservation of our blue planet.
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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.021 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".