Bibliographic record
Abstract
Two recent decisions, one from Australia and one from Canada, should cause us to examine the ethical issues surrounding the regulation of biomedical products. The protection of vulnerable consumers from variable quality and poorly prepared drugs with uncertain parameters of safety and efficacy is a priority for any community and should not have to be weighed against possible costs based on restrictions of trade. However, the possibility of an environment in which the multinational biomedical industry edges out any other players in the treatment of various illnesses has its own dangers. Not least is the apparent collusion between regulators and industry that ramps up the costs and intensity of licensing and risk management so that only an industry-type budget can sustain the costs of compliance. This has the untoward effect of delivering contemporary health care into the hands of those who make immense fortunes out of it. An approach to regulation that tempers bureaucratic mechanisms with a dose of common sense and realistic evidence-based risk assessment could go a long way in avoiding the Scylla and Charybdis awaiting the clinical world in these troubled waters.
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 | 0.017 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.017 | 0.012 |
| Insufficient payload (model declined to judge) | 0.011 | 0.007 |
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".