Leveling up to honour ethical relationality: pedagogical documentation as methodological entanglement
Bibliographic record
Abstract
Education today is not simple nor does it occur in isolation.Educators, now more than ever, are teaching within the global context of calls to action for truth and reconciliation with Indigenous communities around the world and a growing awareness of the damage caused by unsustainable human consumption of the environment.Drawing from an ongoing professional development project involving educators across four childcare centres, this article explores "leveling up" using Pedagogical Documentation and Barad (2007) diffractive thinking to explore new ways to help our human-centred and colonised minds understand Indigenous world views and see ourselves as part of the environment.The way we view PD must be considered critically, knowing that when we work to name, produce, catalyse and move learning forward we must also attend to how various matters have come to matter and how we (as observers and documenters) are part of this relational encounter.What we name as educative in the teaching and learning processes rests on our world view.This article addresses the question: How might leveling up and diffractive methodology inform our use of Pedagogical Documentation and take us beyond traditional human centred and bounded ways of seeing the world and curriculum?
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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 | 0.106 | 0.130 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.017 | 0.149 |
| Scholarly communication | 0.029 | 0.040 |
| Open science | 0.004 | 0.032 |
| Research integrity | 0.005 | 0.011 |
| 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".