Actualizing Reader-Response Theory on L2 Teacher Training Programs
Bibliographic record
Abstract
In this article we share our experiences of using poems in teacher-training courses where the students are predominantly second-language learners. We describe how we tried to help learners engage with a creative text through its language and meaning. We share our experiences of helping to facilitate the open expression of opinions and feelings in L2 teachers (both inservice and preservice) on creative texts, specifically the poem “My Papa’s Waltz” by Theodore Roethke. The use of this poem and others like it in teacher education courses in three of Hong Kong’s tertiary institutions has produced consistently impressive outcomes in terms of teachers’ responses to poetry in general. We aim to illustrate a teaching strategy that emphasizes the reader as expert and to show how this process leads EFL/ESL teachers as well as English-language learners (ELLs) to experience more lived, esthetic responses as part of their coursework.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.049 | 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".