Bibliographic record
Abstract
There is an old and persistent analogy between language and life, which seems to accommodate shifting ideas about what life is and how it came (and comes) to be. In the Bible, Creation is described as if occurring in or at least through language, which is one good reason why medieval Jewish and Christian philosophers believed in etymology more as scientific method than as rhetorical device. In E. R. Curtius's memorable phrase, it constituted a ‘category of thought’ for these men of learning, and was the object of extensive speculation and study, culminating in Isidore of Seville's great encyclopedia of Western knowledge, the Etymologiae. Writing twelve centuries after Isidore, Charles Darwin perceived a ‘curious parallel’ between life and language, quoting the Oxford philologist and Professor of Comparative Theology Max Müller (who was himself applying ideas from Darwin's Origin of Species) in support of his view that ‘The survival or preservation of certain favoured words in the struggle for existence is natural selection’. In language change, Müller had argued, the success of ‘the better, the shorter, the easier forms’ was due to ‘their inherent value’.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.021 | 0.009 |
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".