CRISPR, Like any Other Technology: Shedding Determinism & Reviving Athens
Bibliographic record
Abstract
This article examines current narratives surrounding CRISPR (clustered regularly interspaced short palindromic repeats) and the current Canadian treatment of this novel biotechnology. It argues that Canada’s current approach to genetic research and CRISPR appear to have succumbed to the false narrative of technological determinism. It argues that Canada must buck the narrative and alter the current status quo in two principal ways: Canada should pursue more somatic CRISPR clinical trials in humans and permit pre-clinical germline editing. To design a regulatory regime for clinical germline editing and better guidance on somatic CRISPR clinical trials, Canada should engage Deliberative Polling to ensure Canadians’ views are represented in future legislation and regulations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.061 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.015 | 0.017 |
| 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".