<i>How to chat in English and Chinese: Emerging digital language conventions</i>
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
Rapid changes in language form and function occurring in digital environments present teachers and students of second languages alike with conundrums as to language and discourse standards. Factors affecting the changes that are emerging in digital English include the spatial and temporal possibilities and constraints of the medium, digital facilitation of case-creativity and iconic incorporation, and new social network configurations. This paper analyzes evolving changes in orthographic, syntactic, discourse and sociocultural conventions occurring in English and Chinese in digital environments, based on a small scale study conducted at York University in 2002–2003, noting trends across these languages as well as more limited, culturally and linguistically specific evolutions. The converging conventional changes occurring in these two major world languages suggest that similar transitions are happening generally in languages used for online communication, which has serious implications for second language instruction.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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