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Record W7029794700

Laura Niquay: Vivre et s'affirmer au féminin atikamekw

2017· article· fr· W7029794700 on OpenAlexaboutno aff

Bibliographic record

VenueÉrudit documents and data repository (Érudit Consortium, University of Montreal) · 2017
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)Subject (documents)Context (archaeology)Identity (music)Natural (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

Bonjour! Je vous dis) / Kwei y y y y y y (bis) Je m'appelle Poisson blanc 2 / Atikamekw est mon nom Atikamekw sipik est ma rivire / Je vis au creux de la terre Je vis au creux de la montagne Waratanak 3 / Waratanak!J'ai march dix mille milles Pos mes pas sur les sentiers / O mes parents ont march Je suis millnaire / Millionnaire atikamekw!(Chanson Waratanak, album Waratanak, Laura Niquay 2015) 1 Anthropologue (Ph.D.), Vronique Audet collabore divers projets de recherche, de valorisation et de diffusion concernant les arts et les modes d'tre au monde des Premires Nations et des Inuit au Qubec.Elle est l'auteure du livre Innu nikamu -L'Innu chante : pouvoir des chants, identit et gurison chez les Innus (PUL 2012), ainsi que de nombreux articles connexes.Elle a consacr sa thse de doctorat en anthropologie (Universit de Montral) l'tude ethnographique de la scne musicale populaire autochtone au Qubec (2015).Chercheure postdoctorale au Research Center for Music, Media and Place (MMaP) l'Universit Memorial de Terre-Neuve ainsi qu'au Centre des Premires Nations Nikanite de l'Universit du Qubec Chicoutimi (2015-2017), sa recherche de postdoctorat porte sur le mouvement panautochtone des pow wow qui s'ancre de plus en plus chez les Innus, ainsi que sur les questions d'hritage, de relations et de transformations qui y sont associes.Veronique.audet1

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science 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 score0.543
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0040.002
Scholarly communication0.0010.006
Open science0.0020.003
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 head0.022
GPT teacher head0.256
Teacher spread0.234 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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