Governance and stem cell research; towards the clinic
Bibliographic record
Abstract
This is one of five background papers commissioned for a stem cell research ethics workshop held in Montreal in February 2007, as part of the Canadian Stem Cell Network (SCN) project Towards the Clinic? Ethical, Legal and Social Issues (ELSI) Relevant to Emerging Stem Cell Therapies. In this paper we focus on ELSI issues that are relevant to the governance of stem cell research as it moves towards clinical applications. We have, by and large, focused our attention on the Canadian context--which is complicated enough in its own right--and not tried to provide a comprehensive or comparative international study. Our strategy in this paper is to first give an overview of the context of Canadian stem cell research as it moves toward clinical applications. In Part 1, we identify principal agents and stakeholders and then describe their interests, accountability relationships and interactions. In Part 2, we identify ethical, legal and social issues that seem novel or unique to stem cell research. Most of these involve the derivation and use of embryonic stem cells. Part 3 highlights generic research ethics issues that we deem most pertinent to stem cell research. Finally, in Part 4, we offer some recommendations, most prominent of which is the need to recognise the special opportunity presented by stem cell research for improving ethical governance of health research more generally. Before turning to the context of Canadian stem cell research, it is important to say a bit about what we mean by the governance of such research and how we identified ELSI issues. One thing that we do not mean to imply is that there is or ought to be a single means of governance for all stem cell research in Canada. As noted in Part 1 below, there are multiple institutional actors and stakeholders that are involved in the movement of stem cell research from the bench to the bedside. Many of these have their own governance structures, which are intended to achieve often divergent and competitive organisational objectives. (1) Their interrelationships are complex. We would also note that governance involves the use of various forms of power (legal, bureaucratic, financial, rhetorical, etc.) to bring about results either within an organization or in relation to other organizations. (2) Governance is not only about organizational and inter-organizational lines of authority and accountability; it is also about organizational culture and socialization. Hence, governance involves bottom-up as well as top-down considerations. Our interest is in governance designed to achieve ethical objectives. In many cases, there is a widespread social agreement on ethical objectives. For example, with regard to the ethical treatment of human subjects in research, there is a general consensus that research subjects are volunteers, not conscripts; research should only be conducted when there is sufficient promise of social benefit, the risks to subjects are reasonable and then only with the subjects' consent (or their duly constituted representatives'). Other ethical values are contested, e.g., whether an embryo is entitled to the same protections as human subjects. We note, however, that even when there is consensus around ethical standards, there may still be significant failures in governance arrangements. One of us has argued that this is the case with human subjects protection, claiming in particular that we lack in Canada a demonstrably effective and appropriately accountable evidence-based system of protection. (3) Some of the most challenging governance issues with respect to novel technologies may well be in the most mundane and familiar areas rather than in their novel aspects. We will also argue that even for issues that seem specific to stem cell research, there are important lessons to be learned from earlier developed areas of research-based clinical practice, in particular gene transfer and solid organ transplantation. …
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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 | 0.020 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.021 | 0.064 |
| Scholarly communication | 0.018 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".