Bibliographic record
Abstract
Language is a central area of concern in the twentieth century. This is evident on all sides. First, our century has seen the birth and explosive growth of the science of linguistics. And in a sense ‘explosive’ is the right word, because like the other sciences of man, linguistics is pursued in a number of mutually irreducible ways, according to mutually contradictory approaches, defended by warring schools. There are structuralists in the Bloomfieldian sense, there are proponents of transformational theories, there are formalists. These schools and others have made a big impact. They are not just collections of obscure scholars working far from the public gaze. Names like Jakobson and Chomsky are known far outside the bounds of their discipline. But what is even more striking is the partial hegemony, if one can put it this way, that linguistics has won over other disciplines. From Saussure and the formalists there has developed the whole formidable array of structuralisms, of which Lévi-Strauss is the pathfinder, which seek to explain a whole range of other things: kinship systems, mythologies, fashion (Barthes), the operations of the unconscious (Lacan), with theories drawn in the first place from the study of language. We find terms like ‘paradigm’, ‘syntagm’, ‘metaphor’, ‘metonymy’, used well beyond their original domain.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.018 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".