READING AND WRITING POEMS IN ENGLISH: COLLABORATIVE PRACTICES AT A BRAZILIAN PUBLIC SCHOOL
Bibliographic record
Abstract
ABSTRACT This study, presenting an experience with eighth-grade students at a Brazilian public school, in Goiânia, Goiás, shows students’ ability to collaboratively read and write poems in English. A poem was selected from the Indian-born, Canadian poet Rupi Kaur’s book The sun and her flowers (KAUR, 2017) to discuss and reflect on themes such as love and loss. Firstly, a theoretical reference on the importance of literary texts for English language teaching and the role of collaboration is presented to provide a theoretical basis for this pedagogical practice. The pre-reading, while-reading and post-reading activities are then described and the students’ written productions, based on Rupi Kaur’s poem, are also presented. Through these activities, students enhanced their lexical knowledge of the English language and their creativity, and also interacted with their colleagues to reflect on current issues.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 teacher head, 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".