CANADA’S BIOTECHNOLOGY STRATEGY: STRUGGLES ON THE KNOWLEDGE COMMONS
Bibliographic record
Abstract
This research critically analyses a number of the social, economic,\nenvironmental, and informational questions that attach to biotechnology in the context of Canada’s Biotechnology Strategy. A neo-Marxist biopolitical framework that draws on a number of theoretical elements from autonomist Marxism informs the conceptual scheme. Much like Marx’s methodological orientation based on the perspective of the working class rooted in its own historical activity, contemporary efforts at understanding and situating the current conjuncture of capitalist social relations can be advanced through research into the genealogy of social and political opposition movements. By apprehending these emerging subjectivities we might begin developing a new social vision of our own era. It is precisely those struggles mobilised around biotechnology issues in Canada that this research seeks to elaborate. Drawing on documentary analysis and interviews, the research seeks to determine the role the Canadian Biotechnology Strategy has played in commodifying biotechnology and biotechnological information as part of the social factory, and to interrogate the counter struggles that have emerged to resist the enclosure of the biological and the knowledge commons, with emphasis on the information and knowledge issues encompassed by such struggles. A basic presupposition of this research is that the commodification of biotechnology, as a branch of science that has assumed a central role in production as a source of new knowledge, offers an exemplary case study of both the mobilisation of the social factory in contemporary society and the scope of counter struggles that, themselves, include a variety of information and knowledge issues
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.036 | 0.026 |
| Scholarly communication | 0.018 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| 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".