A decade of regulating agricultural biotechnology liability in Canada : a case study from 1994-2004
Bibliographic record
Abstract
Innovation is the fundamental driver for the advancement of societies. The advent of the Industrial Revolution in the 17th century precipitated a dramatic increase in the rate of innovation. Societies of the time struggled in how to deal with the rapid changes that resulted from these innovations and their application. Present day society is no different. Innovations in today’s society have the ability to be widely adopted and the potential to affect far larger segments of the population that previous innovations. The rapid rise of genetic modification is one such innovation. This innovative technology has been widely adopted by the drug and agriculture industries and as a result, it has impacted all segments of Canadian society. This thesis examines how Canadian society has dealt with the specific innovation of agricultural biotechnology, or the genetic modification of plants. The commercialization of genetically modified plants has resulted in regulatory challenges for the government, intellectual property and liability concerns for industry and consumer acceptance issues within the general public. By researching the interaction and relationships between government regulators, private firms and consumer organizations, it is possible to identify how Canada has reacted to the challenge of regulating agricultural biotechnology. The interdisciplinary framework necessary to accomplish this requires conceptual contributions from economics, political science and sociology. In the development of the innovation, or innovative product, the regulatory approval process requires a risk analysis for all new plant varieties. This risk analysis process is comprised of risk assessment, risk management and risk communication. This thesis argues that risk and the application of risk analysis is appropriate for pre-commercialization, but once the innovative product is in the marketplace, any failure regarding this product can be viewed as a potential liability. The management of and communication about liabilities differs from that of risk management and communication. The key theme of this research is to examine how regulators in Canada have attempted to regulate post-commercialization liabilities and to identify what governance structures or institutions are essential for the regulation of post-commercialization liabilities.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.019 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".