Awakening To Soma Heliakon: Encountering Teacher-Researcher-Learning in the Twenty-First Century
Bibliographic record
Abstract
As two teacher educators and researchers, we explored dimensions of instructional practice in teacher education through online forums. In the course of this research, we drew upon our online interactivity as the basis for reflexive inquiry. Analysis entailed coding key themes to create a four-part rendering involving a hyperlinked poem, a video, a parallaxic praxis research model, and a tagcloud. Interpreting experience through integrated multimedia examples potentially increases learning engagement and provides insights to our belief that teacher education must be deeply mindful, reflective, and interconnected to living. Key words: teacher education, reflexive inquiry, poetic inquiry, parallaxic praxis Les auteures, deux didacticiennes et chercheuses, l’une à la Washington State University et l’autre à l’University of British Columbia, ont exploré diverses facettes des méthodes utilisées dans la formation à l’enseignement à l’aide de forums de discussion. Au cours de cette recher- che, elles se sont appuyées sur leur interactivité en ligne pour nourrir leurs réflexions. Leur ana- lyse comportait le codage des principaux thèmes en vue de créer une représentation quadriparti- te : poème hyperlié, vidéo, modèle de recherche axé sur la parallaxe et nuage de mots clés. L’interprétation des expériences à travers des exemples de multimédia peut favoriser l’implication dans l’apprentissage et s’inscrit dans le droit fil d’une formation à l’enseignement qui, selon les auteures, doit faire place à la réflexion et être branchée sur la vie. Mots clés : formation à l’enseignement, analyse réflexive, analyse poétique, parallaxe.
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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 | 0.015 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.032 | 0.051 |
| Scholarly communication | 0.017 | 0.017 |
| Open science | 0.002 | 0.023 |
| Research integrity | 0.006 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 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".