1 Re-conceptualizing English Language Education through Autobiography: Toward a Pedagogy of Humiliations and Humanness
Bibliographic record
Abstract
This paper considers how English language educators might use autobiography as a pedagogical form to engage their multiple experiences and relations to English and Englishness, and to consider implications for their work. Reflecting on autobiography from this perspective offers possibilities for grappling with our multiple connections and dis-connections to English and Englishness, becoming conscious of the discourses which shape us as educators, and engaging difference in productive and meaningful ways. In undertaking autobiography, we face aspects of ourselves, often aspects that come into conflict. This process of dis-equilibrium has the potential to engender a shift in understanding that helps us to re-conceptualize normative constructions and representations of English language pedagogy. This is a necessary undertaking for educators attempting to work with/in the possibilities of engaging reflectively and critically in English language education. It also offers a space to consider how we might use English ‘appropriately’ in our teachings and engagements. “Any meaning derived from a source outside our acts murders us” (Cooper as cited in Pinar, 2000b, p. 374).
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.037 |
| Scholarly communication | 0.007 | 0.013 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| 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".