Innovation and liability: "Oh no! what have we done?".
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This review article discusses the issues surrounding the biosafety of transgenic crops, their perception by consumers and the matter of socio-economic liability. The issue of liability management regarding transgenics would seem to be related to three key features of present day society. Firstly, consumer trust in government and industry has declined in all industrialized countries. Secondly, regulators in Canada and the United States have adamantly stuck to science-based risk assessment processes while, in Europe, regulators have tried to incorporate socioeconomic factors into the regulatory process. Thirdly, the whole concept of consumer empowerment has been badly dealt with by government, industry and, to a lesser degree, the judiciary. The stakeholders of government and industry have, for the most part, adopted the strategy of ignoring the consumer and hoping their concerns will go away. This hasn't worked and the willingness of the judiciary to hear large class action lawsuits against multinationals has forced reconsideration of this strategy. The key to socioeconomic liability management is to ensure that all stakeholders work together. Even though each stakeholder may have separate agendas, the goal needs to be consensus on the process objectives.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it