Access and Benefit Sharing, Canadian and Aboriginal Research Ethics Policy After the Nagoya Protocol: Digital DNA and Transformations in Biotechnology
Bibliographic record
Abstract
Across the world, the manner in which researchers access genetic resources and associated knowledge of Indigenous and Local Communities (ILCs) is perceived to be problematic. This is due to inequitable practices that implicate asymmetrical power relations between researchers and other stakeholders with these communities. Not only are indigenous knowledge appropriated, ILCs’ conservation ethics in dealing with genetic resources are unrequited. Consequently, a responsive system for equitable access and benefit sharing (ABS) over the utilizations of genetic resources as a combination of economic, conservation and social justice strategy coalesced in the 2010 Nagoya Protocol to the Convention on Biological Diversity. The Article focuses on the ABS dynamic in the context of Aboriginal related research to determine whether extant Canadian research ethics framework requires recalibration pursuant to the emergent global ABS regime mainly symbolized in the Nagoya Protocol and the new challenges posed by current advances in biotechnology with specific regard to the digital DNA phenomenon. While both regimes do not directly pre-empt digital DNA and the malleability of data in research contexts, we conclude that they recognize the evolutionary character of research and knowledge transformations. We argue that they can be interpreted to accommodate the ABS imperatives in these and other emergent contexts. We shed light on how Canadian researchers can effectively navigate the research ethics framework in the Aboriginal contexts given regard to the global ABS regime and the transformations in biotechnology in the post-Nagoya ABS landscape.
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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 | 0.029 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.029 | 0.034 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.011 | 0.008 |
| 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".