He Rawe Tona Kakahu/She Wore a Becoming Dress: Performing the Hyphen
Bibliographic record
Abstract
In the British settler nations of the United States, New Zealand, Australia and Canada, there continues to be debate about how to conduct research across the coloniser-indigene hyphen. Various indigenous scholars have discussed, at length, how western scholarship has been and continues to be implicated in the colonisation of indigenous peoples. While some progress has been made, it continues to be an unresolved issue.\nAs a white American woman, I have responded to this situation by conducting my doctoral research using a decolonising epistemological pluralism that I developed through my practice as an artist and performer. This methodology, which is critical and performative, seeks to dismantle the colonial matrix of power and the dualisms that underpin the hegemony of western knowledge and casts a critical eye on power relations as they manifest out in the world and as they reproduce themselves inside individuals. It is my belief that such an approach will decentre the settler and facilitate working across the hyphen. As an example of how such a methodology could function, I undertook a collaborative and performative research project with Anahera Gildea, a Māori writer and performer from the iwi (tribe) of Ngāti Raukawa ki te Tonga.\nOur research examined the intersection of gender and colonisation. The knowledge systems that we chose to use arose naturally out of who we are and what we know. We are both Butoh performers. We both practice Nichiren Buddhism and use it to guide our daily lives. The outcome of our research was He rawe tona kakahu/She Wore A Becoming Dress, a multimedia Butoh performance, which was performed for two nights at the Film Archive in Wellington, New Zealand in 2009. As a collaboration that worked across the hyphen, we both engaged with critical and decolonising theory from our respective positions on the hyphen, as well as brought our respective world views—I, white American and Anahera, Te Ao Māori . This thesis is an attempt to provide a practice-based understanding of what it was like to undertake research using such a decolonising epistemological pluralism.
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 | 0.002 | 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 | 0.014 | 0.011 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".