Mobile knowledge and the media: The movement of scientific information in the context of environmental controversy
Bibliographic record
Abstract
This paper examines the role of the news media in transnational flows of knowledge. Its focus is on salmon aquaculture, an industry operating in Europe, Canada, and elsewhere. To examine the movement of knowledge from Europe to Canada, a sample of 323 news stories mentioning European aquaculture was drawn from 1261 stories about aquaculture published in Canadian newspapers between 1982 and 2007. Their analysis demonstrates the role of the media in selectively moving and shaping scientific knowledge. This role has been influenced by numerous factors, including journalistic norms, source strategies, and the assertion of trust, relevance and scientific credibility. This analysis corrects the common assumption in the internet era that information flows freely: new technology has not obviated the role of social factors. The media's role in the movement of knowledge also has implications for the geography of science, and for the status of science as a situated practice.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".