Bibliographic record
Abstract
In 2006 the diary of treaty commissioner George MacMartin was found in the Queen’s University Archives in Kingston, Ontario. In it MacMartin records how and under what terms Mushkegowuk and Anishinaabe communities made treaty in 1905—he records that agreement was “accepted” to the terms as “stated.” This primary source is now the central piece of evidence in the Mushkegowuk Council’s legal case that challenges the terms of Treaty No. 9 as written and suggests that what was “stated” never mentioned that these communities would have their land “taken up” for the purposes of development. It is this story of the treaty that playwright Falen Johnson “takes up” for her new play, Treaty no. 9. This article considers how Johnson, through restaging treaty, conceptualizes a new approach to it—one that foregrounds how performance was used and abused in the signing process to facilitate agreement, and one that should be taken account of in the treaty’s current legal case. This article outlines the pragmatic challenges that this approach to treaty might come up against in the court of law and considers how performance studies frameworks and approaches might legitimize the law’s engagement with the repertoire of this treaty as proof.
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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.010 | 0.026 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".