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Record W2790822052 · doi:10.7202/1043702ar

Le folklore des Pays d’en haut au xixe siècle : le témoignage de Marie Caroline Watson Hamlin

2018· article· fr· W2790822052 on OpenAlexaffvenueabout
Marcel Bénéteau

Bibliographic record

VenueFrancophonies d Amérique · 2018
Typearticle
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of Sudbury
Fundersnot available
KeywordsFolkloreHumanitiesArtPolitical science

Abstract

fetched live from OpenAlex

À partir de l’oeuvre de Marie Caroline Watson Hamlin, cet article jette un nouvel éclairage sur le folklore français des Pays d’en haut auxxixeetxxesiècles. Les travaux des historiens des dernières décennies ont produit une meilleure compréhension de l’histoire des Pays d’en haut ainsi que des relations entre leurs populations européennes et amérindiennes. Cependant, nous en savons très peu au sujet du patrimoine immatériel que ces colons, marchands et voyageurs ont amené avec eux. Comment ce folklore a-t-il évolué à l’écart des centres de peuplement de la vallée laurentienne et face aux échanges culturels avec des voisins anglophones et autochtones ? Ce texte propose une étude du folklore de la région du Détroit – établissement relié à la fois aux centres canadiens-français plus à l’est et aux anciens territoires de l’intérieur de l’Empire français – pour reconstituer le folklore perdu des Pays d’en haut. L’ouvrage principal de Watson Hamlin,Legends of le Détroit(1884), se révèle une des sources les plus importantes pour accomplir cette tâche.

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)0.001
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.837
Threshold uncertainty score0.323

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0090.004
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.008
GPT teacher head0.218
Teacher spread0.211 · 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
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
Published2018
Admission routes3
Has abstractyes

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