Bibliographic record
Abstract
Our paper contributes to Science, Technology and Society (STS) scholarship on the practices and technologies of containment. We build on existing work in STS that has analyzed containment as a performative sociotechnical system that generates and sustains new realities, new systems, and new relationships. Our contribution draws from the problem of containment in salmon aquaculture. The stakes for containing salmon are very high. Farmed salmon escapes are environmentally damaging to ecosystems and wild salmon populations, and they put additional pressure on an industry that has a very poor environmental record. We consider in detail Newfoundland and Labrador’s “Code of Containment” that works to keep farmed salmon in cages and prevent them from escaping into the wild. Through our analysis of the Code, we argue that containment is not only about holding inside. It is also about holding together, an obsolete meaning of the term “to contain.” We add to STS scholarship by arguing that containment and its associated Code in Newfoundland holds together a large scale, industrial aquaculture sector that tolerates persistent farmed salmon escapes into the wild from ocean-based cages. We conclude by examining the broader implications of our analysis for STS scholarship on the practices and technologies of containment.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.060 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 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".