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Record W40724045

Francophonies en bord de Meuse: le XVIIIe Congres du CIEF a Liege, 19-26 juin 2004

2016· article· fr· W40724045 on OpenAlexaboutno aff
Congres du Cief, Jean-Pierre Bertrand

Bibliographic record

Venuenot available
Typearticle
Languagefr
FieldArts and Humanities
TopicCultural Identity and Heritage
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtFrench
DOInot available

Abstract

fetched live from OpenAlex

Apres avoir traverse les continents et fait escale dans les principa les villes francophone ou francophiles du mo de, de La Guadeloup a Montreal, de la Nouvelle Orleans a Abidjan, de Portland a Toulouse, il etait dans la logique des choses que le CIEF se pose un jour en Commu naute franchise de Belgique, haut lieu de la francophonie. II etait peut-etre moins evident que Liege soit choisie: certes la metropole wallonne a tous les ressorts dune grande cite francophone, mais timidement connue, elle n'a pas Laura des quelques autres villes, flamandes pour la plupart Bruges, Gand, Anvers, Bruxelles aussi en lesquelles cristallise ce qu on appelait jusqu au debut du vingtieme siecle encore Lame beige. Liege est comme farouchement reveche a cette mythologie-la, qui met dans le meme sac le chocolat, les moules, les frites, Jacques Brel et Eddy Merckx, et donne a la Belgique un sentiment d'unite aussi reel qu imaginaire. Trop wallonne, trop franchise (on y fete chaque annee le 14 juillet), la ville en bord de Meuse, peut-etre par reflexe principautaire, tient a conserver ses marques: elle a ses boulets et son peket, comme dautres ont leurs boulettes et leur goutte, mais en renommant son quotidien, elle en change les contours et lui donne une saveur qui n est pas que folklorique. II faut y vivre quelque peu pour sentir cette ambiance et c est peut-etre inconsciemment la raison qui a guide les organisatrices du CIEF a venir y etablir les quartiers du

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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.403
Threshold uncertainty score0.801

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.002
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0340.003

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 head0.016
GPT teacher head0.223
Teacher spread0.207 · 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
GenreOther

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
Published2016
Admission routes1
Has abstractyes

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