Bibliographic record
Abstract
The theory of terminology was developed by the founder of the Vienna school, Wuster, on objectivist foundations (a term as a linguistic symbol formed by words or elements of words, the structured nature of the vocabulary) with the aim of standardising the concepts and terms. The main schools of the theory of terminology were established approximately at the same time in Vienna, Prague, and Moscow and later also in Quebec. Czech terminography derives its tradition from the Prague Linguistic Circle (Havranek, Roudny, Tejnor, Kocourek), whose aim was the structural and functional description of specialised language and the standardisation of terminology by authoritative institutions. Its concept of specialised language as part of specialised communication was developed in the 1970s in connection with the communicative and pragmatic orientation of linguistics as a socioterminological trend (in France and Canada). Modern terminology moves from an onomasiological approach to a communicative one (Sager); more recently use is made of the findings of cognitive science and of language corpora for the collection of excerpts (Temmerman).
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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".