Bibliographic record
Abstract
Si les non-conséquentialistes veulent adhérer à l'exigence d'universalisabilité, alors ils devront adopter une prise de position étonnamment relativiste. Non seulement vont-ils affirmer, dans une veine familière, que les prémisses invoquées dans l'argumentation morale n'ont de force que relative à l'agent, c'est-à-dire qu'elles peuvent impliquer l'usage d'un indexical — comme dans la considération que cette option-ci ou celle-là favoriserait mes engagements, me délesterait de mes devoirs ou bénéficierait à mes enfants — et qu'elles ne peuvent fournir de raisons qu'à l'agent indexicalement pertinent, moi-même en l'occurrence. Ils devront aussi interpréter la considération invoquée dans les conclusions morales typiques, selon laquelle telle ou telle option est juste ou devrait être choisie ou peu importe, comme n'ayant elle-même qu'une force relative à l'agent.
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 | 0.019 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.046 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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".