Bibliographic record
Abstract
Based on Halliday’s theory of register, this paper concerns about marked code-switching from the perspective of sociolinguistic situational context. Marked code-switching does not happen at random, but a kind of rational behavior. The data are gathered from utterances occurred in different situational contexts, by which and based on the field, tenor and mode of register, this research has made a deep analysis on marked code-switch, its socio-pragmatic functions and psychological motivations as well. It does have some research value either in theory and application since there is seldom research done about the marked code-switching phenomenon from the perspective of register theory. Keywords: register theory; marked code-switching; socio-pragmatic functions Resume: Sur la base de la theorie de registre de Halliday, cet article s’interesse sur le code-switching marque a partir de la perspective du contexte situationnel sociolinguistique. Le Code-switching marque ne se fait pas au hasard. C’est une sorte de procede rationnel. Les donnees sont recueillies a partir des enonces produits dans de differents contextes situationnels et la recherche a fait une analyse profonde sur le code-switching marque, ses fonctions socio-pragmatiques et aussi les motivations psychologiques. Elle possede une certaine valeur de recherche dans la theorie et dans l'application, car les recherches sur le phenomene de code-switching marque sont rarement faites dans la perspective de la theorie de registre. Mots-cles: la theorie de register; le code-switching marque; les fonctions socio-pragmatiques 摘 要：本文從社會語言學的情景語境角度，借助Halliday的語域理論探討在語言的使用中有標記語碼轉換現象。 有標記語碼轉換不是盲目隨意的，而是一種理性行為。本文以一些生活中的情景語境片段為語料，從語域理論的語場、語勢和語式三維變項角度分析了有標記語碼轉換現象、有標記語碼轉換的社會語用和心理動機。將語域理論用於研究有標記語碼轉換的研究不甚多見，因此本研究具有一定的理論和應用價值。 關鍵詞：語域理論；有標記語碼轉換；社會語用功能
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 | 0.009 |
| 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 | 0.006 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".