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Record W1505025684 · doi:10.3138/tric.35.2.185

Performing Cultural Crossroads: The Subject-Making Functions of “I am” Declarations in Daniel David Moses’s <i>Almighty Voice and His Wife</i>

2014· article· en· W1505025684 on OpenAlexaffvenueabout
Kailin Wright

Bibliographic record

VenueTheatre Research in Canada · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsWifePerformative utteranceLegendMythologySubject (documents)SociologyWhite (mutation)NarrativeDramaLiteratureHistoryArtPhilosophyAestheticsTheologyComputer science

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.803
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.047
GPT teacher head0.328
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2014
Admission routes3
Has abstractyes

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