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Record W2972014719 · doi:10.1590/1980-4369e2019022

Les almanachs francophones dans les Amériques: transferts, structures, évolutions

2019· article· fr· W2972014719 on OpenAlexaboutno aff
Hans-Jürgen Lűsebrink

Bibliographic record

VenueHistória (São Paulo) · 2019
Typearticle
Languagefr
FieldSocial Sciences
TopicHistorical and Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

RÉSUMÉ Le genre éditorial de l’almanach fit son entrée en Amérique avec la colonisation. Introduits en 1777 en Nouvelle France, avec l’Almanach Encyclopédique (Montréal) à la fin du XVIIIe siècle, en Louisiane au début du XIXe siècle, en Haiti et dans les Antilles françaises, puis en Nouvelle-Angleterre, en Californie et dans l’Ouest du Canada à partir du milieu du XIXe siècle, les almanachs francophones sont issus de processus de transferts culturels qui transformèrent successivement ce genre aux facettes multiples. Constituant le genre imprimé le plus répandu dans les sociétés des XVIIe au XIXe siècles, l’almanach revêtit des formes et des fonctions très diverses: les almanachs de large circulation comme le Guide du cultivateur (1830-1830) ou l’Almanach du peuple (1856) au Québec représentaient à l’époque souvent le seul imprimé diffusé parmi les couches populaires, à côté d’écrits religieux, tandis que l’Almanach des Dames (Nouvelle Orléans, XIXe siècle) ou l’Almanach Royal d’Haiti (1810-1815), par exemple, remplirent des fonctions spécifiques destinées à des publics élitistes. Le but de cet article est de dresser un tableau d’ensemble des formes, des fonctions sociales et de l’évolution de ce genre de première importance que représenta l’almanach dans les cultures médiatiques francophones dans les Amériques jusque dans les années 1920.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score0.843

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0050.002
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.025
GPT teacher head0.264
Teacher spread0.239 · 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 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

Citations2
Published2019
Admission routes1
Has abstractyes

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