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Record W2620093003 · doi:10.7202/1039655ar

Singing For Frog Plain

2017· article· en· W2620093003 on OpenAlexvenueaboutno aff
Monique Giroux

Bibliographic record

VenueEthnologies · 2017
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
FundersMinistry of Economy, Trade and Industry
KeywordsMetisFalconHistoryIndigenousIdentity (music)The ImaginaryGenealogyEthnologyArtPsychologyEcologyAesthetics

Abstract

fetched live from OpenAlex

Pierre Falcon is the earliest known Metis composer. Born in 1793 in Fort La Coude (Elbow Fort) in what is now west-central Manitoba, his adult life spanned the “Golden Years” (Shore 2001) of the western Metis nation. Known as the Bard of the Prairies, Falcon’s songs drew on events of local importance during this period, providing a means to remember and share Metis history, and to solidify a sense of Metis nationalism. Beginning in the late-1800s historians, novelists, folklorists, journalists, and musicians began turning their attention to Falcon, resulting in a strikingly large number of popular and academic references to his life and songs. While these references are varied, together they tell a story about the relationship between Canada and the Metis Nation. On the one hand, references to Falcon often draw from, and in fact help create, images of the Imaginary Indian (Francis 1992). Yet on the other hand, many references to Falcon erase his Indigeneity, or blend his Metis identity seamlessly into a Franco-Manitoban, or western Canadian identity. These seemingly contradictory representations, as I will argue in this paper, ultimately point to the ambiguous positioning of Metis people as Indigenous peoples, and speak to an obsession with mixed-ness that denies the Metis their full and authentic Indigeneity.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.384
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0150.000
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 head0.122
GPT teacher head0.454
Teacher spread0.331 · 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
Published2017
Admission routes2
Has abstractyes

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