Bibliographic record
Abstract
“A valuable and timely collection.” —Alan D. Filewod, author of Committing Theatre Following the Final Report on Truth and Reconciliation, Performing Turtle Island investigates theatre as a tool for community engagement, education, and resistance. Understanding Indigenous cultures as critical sources of knowledge and meaning, each essay addresses issues that remind us that the way to reconciliation between Canadians and Indigenous peoples is neither straightforward nor easily achieved. Comprised of multidisciplinary and diverse perspectives, Performing Turtle Island considers performance as both a means to self-empowerment and self-determination, and a way of placing Indigenous performance in dialogue with other nations, both on the lands of Turtle Island and on the world stage. “Brilliantly introduces pedagogies that jump scale; a bundling project for future ancestors revealing knowledges for flight into kinstillatory relationships.” —Karyn Recollet, co-author of In This Together: Blackness, Indigeneity, and Hip Hop “An important resource for those who want to introduce or incorporate Indigenous artistic perspectives in their course or work.” —Heather Davis-Fisch, author of Loss and Cultural Remains in Performance “A very significant and welcome contribution to the growing body of work on Indigenous theatre and performance in the land now called Canada.” —Ric Knowles, author of Performing the Intercultural City
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.086 | 0.018 |
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".