Performing Cultural Crossroads: The Subject-Making Functions of “I am” Declarations in Daniel David Moses’s <i>Almighty Voice and His Wife</i>
Bibliographic record
Abstract
Daniel David Moses’s Almighty Voice and His Wife tells the legend of a Cree man who lived in Saskatchewan during the end of the nineteenth century. After being arrested for killing a cow, he escaped prison and died in a shootout with over one hundred Mounted police. This essay explores the performed transmission of “I am” declarations in encounters between historical Indigenous figures and perceived white colonial audiences in Moses’s play. In a work that seeks to reshape earlier versions of the Almighty Voice myth, performative utterances are a key strategy for speaking back to colonial legends and a history of enforced Christianity in Canada. Almighty Voice features a series of “I am” statements, such as “I’m no ghost” and “I am the wife of Almighty Voice;” yet, the final attempt at selfassertion—“ Who am I?”—does not leave the audience with truth claims but with questions. Integrating J. L. Austin’s concept of speech acts with Judith Butler’s performative identity theory and Miri Albahari’s theory of possessive subjecthood, this paper outlines four main functions of “I am” statements: 1) to constitute the self; 2) to perform belongingness; 3) to assert ownership over identificatory categories; and 4) to emphasize individuality. The conclusion returns to the larger questions of the subject-making capacities of self-narration in Canadian drama.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.035 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".