Toward an unsettling curriculum of care writing & care creation: A “complicated conversation”
Bibliographic record
Abstract
While recent scholarly attention has been focused on deepening care ethics’ interdisciplinary conceptualizations, research has yet to attend to relationships between care and writing, and care and creation. This paper, cognizant also of a global devaluation of care in neoliberal times, thus originally introduces and conceptualizes possibilities toward a curriculum of “care writing” and “care creation.” We, three faculty members and three middle and secondary English language arts schoolteachers, share a year-long “complicated conversation” of online bimonthly dialogue, in which we envision care’s enactment in and through multimodal, multilingual, and plurilingual writing practices in educational sites of learning. Additionally, we introduce care creation as a research methodology informed by research creation. Our aim is to underscore the significance of bringing an ethics of care into writing and creation, and conversely, in bringing care to life and life to care in curriculum studies and school contexts in increasingly fraught times.
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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 | 0.019 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.071 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".