Bibliographic record
Abstract
We, SKRIB: Critical Studies in Writing Programs and Pedagogy co-editors, and the editorial board are pleased to provide a space for multilingual, international writing scholars and practitioners. As we wrote on the founding of the journal, our hope for SKRIB is to facilitate “intercultural dialogue around the development of writing programmes, writing centres, and writing pedagogy in post-secondary institutions of higher learning around the world.” As a forum for intercultural discourse, SKRIB draws attention to the ways in which the writing at the core of our work is not neutral, but rather deeply personal, and it resides in an inherently politicized space. Our work is always necessarily caught up in globalization processes and global contestations of power between nation states, ideologies, cultures, communities, and languages. SKRIB invites scholars to centre this conception of writing as inherently political in the ways they critically reflect on their writing programs, pedagogies, and initiatives, and, especially, in how they contribute to the development of writing studies; decolonization, equity, inclusion, and diversity are fundamental responsibilities of writing teachers, scholars, and administrators.
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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 | 0.011 | 0.052 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.016 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.071 | 0.041 |
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".