Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This article explores the possibilities and limitations of the sociolinguistic notion of code-switching for the analysis of multilingual texts, in particular those belonging to literature as it is commonly understood (prose fiction, drama and poetry). In such (con)texts, I argue, code-switching is ‘staged’: produced rather than reproduced. Even when texts stage bilingual conversations with the aim of imitating real-life speech events, mimesis is mediated by the shift from spoken to written mode, which contrasts with the presence and proximity typical of (spoken) verbal interaction. While this mediation limits the applicability of sociolinguistic notions when discussing literary corpora, several examples from both North America (Junot Díaz, Gloria Anzaldúa and Ana Lydia Vega) and Europe (Lydie Salvayre, Ágota Kristóf, Franz Kafka and Leo Tolstoy) show how literary texts ‘stage’ code-switching.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it