Opening the door to writing re<i>lation</i>alities: Moving writing and the teaching of writing
Bibliographic record
Abstract
Abstract As writers are increasingly required to leave their ways of knowing, doing and being at the doors of their classrooms, this article explores what happens when teachers of writers open those doors and mobilize the Writing Realities framework's interrelated principles of writer‐identity , critical literacies , culturally sustaining pedagogy , multiliteracies , translanguaging and intertextuality . With examples from place‐writing and place‐walking experiences with educators in a Summer Writing Institute, we show the possibilities and potential for multiple and diverse writing realities and re lational ities. The article explores how writing re lation alities moves outward from those moments to (re)energize teachers to (re)engage in the pressing work of challenging the issues of equity and power in classrooms, and to know/be/teach writers/writing differently.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.037 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".