Learning How to “Do”: Creating Spaces for “The Missing” inLanguage and Literacy Curricula and Research
Bibliographic record
Abstract
Show me how to do like you Show me how to do it"And so begins Alice Walker's (1982) The Color Purple.Walker's epigraph connects to the novel's heroine, Celie, by suggesting that she desires/requires a model for how to live her life with pride-a model that is perhaps provided in the form of the beautiful songstress, Shug Avery.I (Rachel) had always read this epigraph with the hope that it might equally propose that if we readers pay attention to the workings-out of Celie's sufferings and pleasures, we might just learn a thing or two about courage and survival.When I was teaching in schools and in my introduction to academia, I transferred this reading to the context of my own life, making "Show me how to do like you/Show me how to do it" the plea I could address to those I perceived as master pedagogues when my own students turned and faced me with a way to learn.I (Luigi) also came to academia with fantasies of finding someone who knew how to do it.Perfection in teaching was never something I believed to be attainable, however, I was sure that an "expert" could provide me with a model of how to "be" in teaching.If it weren't for
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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 | 0.012 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.025 |
| Scholarly communication | 0.022 | 0.028 |
| Open science | 0.003 | 0.023 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".