Bibliographic record
Abstract
To cite: Schuklenk U. J Med Ethics 2013;39:303–306. ABSTRACT This article analyses, from a bioethics journal editor’s perspective, the threats to academic freedom and freedom of expression that academic bioethicists and academic bioethics journals are subjected to by political activists applying pressure from outside of the academy. I defend bioethicists’ academic freedom to reach and defend conclusions many find offensive and ‘wrong’. However, I also support the view that academics arguing controversial matters such as, for instance, the moral legitimacy of infanticide should take clear responsibility for the views they defend and should not try to hide behind analytical philosophers’ rationales such as wanting to test an argument for the sake of testing an argument. This article proposes that bioethics journals establish higher-quality requirements and more stringent mechanisms of peer review than usual for iconoclastic articles.
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 | 0.105 | 0.361 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.019 | 0.037 |
| Scholarly communication | 0.067 | 0.048 |
| Open science | 0.004 | 0.022 |
| Research integrity | 0.047 | 0.030 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".