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Record W6941457826 · doi:10.1285/i22390359v53p321

La narration collective chez les Cowboys Fringants: Représentations sociales et mise en scène de soi

2022· dataset· en· W6941457826 on OpenAlexaboutno aff

Bibliographic record

VenueUniversità del Salento · 2022
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeMusicalPresentation (obstetrics)FrenchContext (archaeology)Snapshot (computer storage)Social identity theory

Abstract

fetched live from OpenAlex

From the very beginning, the Cowboys Fringants, among the greatest exponents of Quebec folk-rock of the last twenty years, have composed songs that reflect their social and geographical environment. Particularly prolific in their musical production, the band appears to be very tied to its community of origin, as evidenced by the numerous topics dealt with relating to Quebec, its territories, and its language. The abundant corpus of songs composed over the years therefore allows for exploration of the contribution of the band to both social representations of the Franco-Quebec community and co-construction of the sense of belonging to the latter. After a presentation of the historical and sociolinguistic context of the sole province in Canada with a majority francophone population, followed by brief methodological notes relating to the treatment of the corpus – which includes all the albums published until 2021 – the study will focus on the places and the protagonists described by the group. The sociocultural snapshot created therein will therefore allow investigation and reflection on the collective identity thus (self) represented, to understand how this narrative allows the band to actively participate in the co-construction of the social representations of Quebecers.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.558
Threshold uncertainty score0.879

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.005
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.010

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 head0.024
GPT teacher head0.264
Teacher spread0.240 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreDataset

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
Published2022
Admission routes1
Has abstractyes

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