Bibliographic record
Abstract
This article makes a case for the importance of integrating public writing pedagogy in and beyond second language (L2) writing classrooms. Public writing is defined as a situated, distributed act of engaging public audiences through writing, with various semiotic resources and modalities, to make meaning, connect, and bring about social change. L2 writers practice public writing deliberately or unwittingly, for various personal or political purposes, and within various discursive contexts. However, such practices are underresearched, undertheorized, and underdiscussed in L2 writing classrooms, which could be partially ascribed to the disciplinary disposition of the field L2 writing and to the ethical concerns regarding cultural assimilation. The article begins by contextualizing the definitions of public writing in relation to L2 writing. It then explains why it is important to discuss public writing in an L2 writing classroom and consider public writing a legitimate L2 writing issue while acknowledging the pedagogical resistance. In particular, the article highlights the decolonial potential of practicing public writing in an L2. In the final section, the article offers pedagogical guidelines and a graphic framework concerning the “where” and “how” of teaching public writing in an L2.
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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.019 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".