Bibliographic record
Abstract
1) ‘“Be true to yourself!” and “Don't cave in!” express the value people place on [_]….’ 2) ‘… an important sense of [_] is being true to oneself.’ 3) ‘[_] encourages and protects people's general capacity to lead their lives out of a distinctive sense of their own character, a sense of what is important to and for them. ’ 4) ‘… to value [_] is to place value on an agent's acting from her reasons, whether they are good ones or not.’ Quiz: fill in the blanks. Here is a hint: two are autonomy and two are integrity. Can you sort out which ones are which? I suspect not, especially since the first two are nearly identical but have different answers. The third seems clearly to be integrity, at least given what philosophers such as Bernard Williams write about integrity: that it involves preserving one's own distinct character. However, the answer to 3) is autonomy. The fourth quotation brings to mind discussions about how autonomous agents can make bad choices, but we respect their autonomy by allowing them to do so. However, the answer to 4) is integrity.
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 | 0.015 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.079 |
| Scholarly communication | 0.011 | 0.036 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.010 | 0.017 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".