Troubling the Training: A Reflexive Dialogue on Decolonizing Performance Pedagogies in the Philippines and Malaysia
Bibliographic record
Abstract
Where should we begin a dialogue about decolonizing and reimagining performance pedagogies in the Southeast Asian context? We first met when we were completing the Choreomundus International MA in Dance Knowledge, Practice, and Heritage in Europe and we are now pursuing our PhD degrees in Australia and Canada. Our dialogue opens by offering a contextualization of land grabbing and the exploitation of resources in the Philippines before delving into the relationship between land and body through careful reflection on our own bodily training. We are convinced that violence against land and body can be undone only through Indigenous sovereignty, by mobilizing the intergenerational knowledge that resides in Indigenous bodies. Decolonizing pedagogies enable an unlearning of the ways in which colonialism has been written on bodies. Integration as a decolonial method is not only about integrating performance elements, but is also about shifting towards a pedagogy of performance that empowers the Indigenous, minorities, and the marginalized, and integrates their clamor for land, social justice, and equity in the process of recreating cultural performances. By situating our personal journeys within the social and political contexts of our home countries and of the countries in which we have been educated, we hope that this dialogue offers an intimate consideration of what non-Indigenous and postcolonial scholars can contribute to the conversation around decolonizing performance pedagogies.
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.
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 | 0.031 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.026 | 0.053 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.004 | 0.020 |
| Research integrity | 0.007 | 0.021 |
| Insufficient payload (model declined to judge) | 0.003 | 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".