I Hate Writing: Making a Case for the Creation of Graphic Novels in the Caribbean English Classroom to Develop Students’ Creative Writing Skills
Bibliographic record
Abstract
Caribbean students are repeatedly engaged in rigid forms of writing to meet the requirements of external exams, which often leads to negative attitudes to writing. With current shifts to multimodal and multi-literate texts to engage students’ multiple literacies in learning, students’ creation of graphic novels in Caribbean English classrooms can enable their engagement in meaningful creative writing. To illustrate this, I draw on my recent experiences with four inner-city boys at a Jamaican high school who showed marked improvement in their attitudes and their creative writing skills after creating graphic novels. The preliminary findings from my research suggest a need for more personalised learning strategies and for more opportunities for students to use their home language in Caribbean classrooms.
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.020 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".