Auto/ethno/graphies as Teaching Lives: An Aesthetics of Difference
Bibliographic record
Abstract
In the midst of the everyday of academia, two teaching lives collide in an office doorway, tentatively exchanging stories of students' language "art"-each sparked by the other's interest in the aesthetic of pedagogy. These intersectings of "knowing and not knowing" conspire in our lives to begin a daunting journey of evoking in teachers-to-be aesthetic possibilities in the teaching of language arts. We share the personal scriptings and scripts of our teaching lives, exposing both the vulnerabilities and the possibilities of the arts for our selves and our students in the pre-service language arts classroom. We draw from qualitative methodologies that work with biography, autobiography, and ethnography settling with "auto/ethno/graphy" to unsettle the scripts of hegemonic discourse. Clear your desk. Dip your brush...About the AuthorsCynthia M. Morawski is an associate professor of Education at the University of Ottawa, Canada. Her research interests include literacy and integrated arts, learning differences, and bibliotherapy. She is particularly interested in the intrapersonal dimensions of learning and employs multiple expressions and representations in teaching and research. Correspondence to C. Morawski, Faculty of Education, University of Ottawa, 145 Jean-Jacques Lussier, Ottawa, Ontario K1N 6N5. E-mail: morawski@uottawa.ca Pat Palulis is an assistant professor of Education at the University of Ottawa, Canada. Her research interests include curriculum theorizing in language, literacy, culture, and spatiality; post-structural and post-colonial discourses; intertextuality; performative auto/ethno/graphy related to teaching lives and praxis. Correspondence to P. Palulis, Faculty of Education, University of Ottawa, 145 Jean-Jacques Lussier, Ottawa, Ontario K1N 6N5. E-mail: ppalulis@uottawa.ca
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.086 |
| Scholarly communication | 0.013 | 0.017 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".