Bibliographic record
Abstract
For nineteenth century British scientific naturalists like Charles Darwin, Thomas Henry Huxley, and John Tyndall, translation, and the issues of language that it raised, were crucial. Dealing with these issues became a major part of their strategy to reform British science, and it involved opening up the scientific community to French and German research. Early in their careers, both Huxley and Tyndall invested time translating science books from the continent into English. Later, as they themselves wrote books that were in demand across the channel, they, and Darwin, put a great deal of time and energy into locating the best possible translators for their writings. Translation was not only a key to reforming British science; it was also essential as a means of circulating the evolutionary worldview of scientific naturalism globally. But Darwin, Huxley, and Tyndall were not fully prepared for the challenges they would encounter in authorizing translations of their own works.
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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.041 |
| Scholarly communication | 0.017 | 0.014 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.021 | 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".