"A TSUNAMI WAVE OF SCIENCE": HOW THE TECHNOLOGIES OF TRANSHUMANIST MEDICINE ARE SHIFTING CANADA'S HEALTH RESEARCH AGENDA
Bibliographic record
Abstract
This article begins with an examination of a growing movement known as transhumanism. With thousands of members from various backgrounds and academic disciplines assembled at prestigious institutions around the world, this group is morally committed to the idea that technology ought to be used to radically alter the human condition. While the transhumanist stance may appear to be radical, in this article it is argued that the project of transhumanist medicine is to be taken seriously because its underlying philosophies are already embedded in the mainstream North American health research agenda, resulting in a recent shift towards medicine. In Part I, the authors briefly outline the core principles and practices of transhumanism. In Part II of the article, they examine nanotechnology as transhumanism's technologies of choice, illustrating the transhumanist vision of medical science as a self-enabled, interventionist, enhancement-focused enterprise. In Part III, the authors examine a shift in agenda in Canadian federal research and development towards an enhancement-focused medical science. Finally, in Part IV, there are two possible implications suggested for this shift towards a transhumanist medicine. While emerging and future human enhancement technologies may well have much to offer, Canada's health research agenda is shifting towards a self-enabled, interventionist, enhancement-focused enterprise without pausing to consider or address its underlying philosophies or implications. In conclusion, this brief article suggests that there are significant ramifications in doing so, both in terms of our core conceptions of what health is and in our sense of entitlement to it. Although this article offers no concrete answers to these issues, this work is intended as the preface to an enduring discourse that is long overdue in Canadian bioethics, health law and policy.
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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 | 0.015 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.038 | 0.043 |
| Scholarly communication | 0.023 | 0.009 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.010 | 0.014 |
| 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".