Bibliographic record
Abstract
Corpus-based language research has been long prospered since the middle of last century. Corpus is therefore frequently used in foreign language (mostly English) teaching and research due to the fundamental principles of modern Corpus Linguistics along with the colorful resources of word-banks and the corresponding tools, especially in western countries. In China, the related literature found its way from introducing the foreign researches to our own practice into this field. As a conclusion, corpus and Corpus Linguistics can be closely connected with and widely applied in foreign language teaching and research with a predictable bright future. Keywords: corpus, Corpus Linguistics, foreign language teaching and research Resume Le moyen de recherches sur le corpus a connu un developpement rapide depuis le milieu du siecle precedent et a atteint la maturite aujourd’hui. En raison de l’importance de la linguistique de corpus et de la methode de recherches sur le corppus, et etant donne ses ressources riches ainsi que les facilites apportees par les outils de recherche, le corpus est appliquee amplement dans les recherches linguistiques notamment dans celles de l’anglais. A l’etranger, l’etude de la linguistique de corpus a debute tot et a donne beaucoup de fruits ; le travail du milieu des langues etrangeres chinois dans ce domaine a commence par la presentation du corpus etranger et sa situation d’etude, et puis procede a des applications pratiques. En somme, il existe des relations etroites et diverses entre le corpus et les recherches de l’enseignement-apprentissage des langues etrangeres, et les recherches de l’enseignement-apprentissage des langues etrangeres basant sur le corpus presente une bonne perspective. Mots-cles: corpus, linguistique de corpus, recherches de l’enseignement-apprentissage des langues etrangeres 摘 要 語料庫研究方法自上個世紀中葉以來迅速發展，到今天已空前繁榮。由於語料庫語言學和語料庫研究方法的重要性，又由於豐富的語料庫資源及檢索工具提供了實踐的可能和便利，語料庫被廣泛應用於語言研究特別是英語教學研究中。國外語料庫語言學研究起步早，成果多；我國外語界在這方面的工作主要是從介紹國外語料庫及其研究現狀開始，然後進行一些應用實踐。總之，語料庫與外語教學研究有著緊密的、多層面的關係，基於語料庫的外語教學研究大有可為、前景廣闊。 關鍵詞：語料庫；語料庫語言學；外語教學研究
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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 | 0.026 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.019 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.014 | 0.018 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".