Unsettling allyship, unlearning and learning towards decolonising solidarity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Social movements are pedagogical spaces for collective learning across difference. Divergent worldviews, interest and identity, historical legacies and relations of power complicate notions of allyship and solidarity for common cause. In this article, we draw on social movement and transformative learning to reflect on our experiences of learning and unlearning as white settler-colonialists researching allyship in the Standing Rock struggle against an oil pipeline in the United States. Our text is also shaped by our own experience as activists within a local Indigenous-led movement to protect ocean and land from the Trudeau–Kinder Morgan oil pipeline. First we introduce ourselves, our research project, context and argument. We then position our work within social movement and transformative learning scholarship, critique notions of allyship and then solidarity. We argue for the unlearning of colonial practices and mindsets which centre our particular white colonial knowledge, leadership, privilege, power and bodies and learning towards decolonising solidarity. To illustrate this process, we present three personal vignettes that speak about the start of our own 'unlearning of ourselves', and learning of decolonising solidarity. We conclude the article with a discussion of how best we believe learning towards decolonising solidarity might proceed in social movements.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it