Reading between the "Frames": English Language Learners' and non-English Language Learners' Responses to Graphic Novels
Bibliographic record
Abstract
Literacy in the 21st century is constantly evolving. To teach literacy effectively, educators need to embrace and understand linguistic, cultural and textual practices that are relevant for students. Reading and responding to graphic novels in face-to-face and online settings are such 21st century literate practices. This thesis focuses on how grade 6 students who are both English Language Learners and non-English Language Learners respond and connect to social justice issues in graphic novels through literature circles, online blogging and personal journals. Responses to social justice issues were fairly similar between English Language Learners and non-English Language Learners, especially based on a cultural experience standpoint. It is important for educators to encourage students to connect with prior experiences and knowledge with social justice issues and stereotypes that exist in their own world. This prepares students to become more socially conscious and critical thinkers about the world around them.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".