A Settler Duoethnography About Allyship in an Era of Reconciliation
Bibliographic record
Abstract
As settler women, former teachers in First Nation communities, and scholars working in Indigenous education, we are responsible for engaging in the complexities of reconciliation through an allyship framework. In this article, we use duoethnography to critically engage in dialogue around the practice of allyship. In revisiting formative moments in our individual and collective teaching and research journey, we wade through some of the current tensions around solidarity work, problematizing the performative and binary approaches to allyship we see increasingly propagated across academic institutions and social groups. This critical dialogue illuminates how we might rethink becoming stronger collaborators with Indigenous people and engage others in exploring their allyship practice. Keywords: duoethnography, Indigenous education, allyship, reconciliation En tant que femmes colons, anciennes enseignantes dans des communautés des Premières nations et universitaires travaillant dans le domaine de l'éducation autochtone, nous avons la responsabilité de nous engager dans les complexités de la réconciliation à travers un cadre d'alliés. Dans cet article, nous utilisons la duoethnographie pour engager un dialogue critique sur la pratique d’agir comme allié. En revisitant les moments formateurs de notre parcours individuel et collectif d'enseignement et de recherche, nous nous frayons un chemin à travers certaines des tensions actuelles autour du travail de solidarité, en problématisant les approches performatives et binaires de l'allié que nous voyons de plus en plus propagées dans les institutions académiques et les groupes sociaux. Ce dialogue critique met en lumière la manière dont nous pourrions repenser à devenir des collaborateurs plus solides avec les peuples autochtones et inciter les autres à explorer leur pratique d'agir comme allié. Mots-clés : duoethnographie, éducation autochtone, allié, réconciliation
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 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 teacher head, 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".