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Record W3034347309 · doi:10.4000/books.pub.13988

C’était demain : anticiper la science-fiction en France et au Quebec (1880-1950)

2018· book· fr· W3034347309 on OpenAlexaboutno aff

Bibliographic record

VenuePresses Universitaires de Bordeaux eBooks · 2018
Typebook
Languagefr
FieldSocial Sciences
TopicHistorical and Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtMerge (version control)Computer science

Abstract

fetched live from OpenAlex

L’écriture des futurs possibles n’a pas attendu le xxe siècle pour exister. Née avec la Révolution industrielle et les progrès techniques, la science-fiction ne s’appelait pas encore ainsi : les récits évoquant l’avenir appartenaient à la littérature conjecturale selon le mot de Pierre Versins, à la proto-science-fiction, à l’anticipation ou au merveilleux scientifique. Entre 1880 et 1950 émerge un continent littéraire français et francophone qu’il faut explorer, héritier de Jules Verne et contemporain de H. G. Wells. Ce ne sont pas des générations perdues mais des écrivains à la créativité singulière qui ont su articuler utopie, aventures, science et voyages extraordinaires tout en vivant une fin de xixe siècle dynamisée paradoxalement par l’essor scientifique et la lame de fond de la Première Guerre mondiale. L’utopie, l’apocalypse, les anticipations technologiques et la fascination pour la science sont les soubassements d’une galaxie littéraire bien présente au Canada francophone et en France, diffusée par un dense réseau de presse quotidienne et spécialisée. De Paul d’Ivoi à René Barjavel, des effets spéciaux de Georges Méliès aux rêveries cosmiques de Camille Flammarion, cet ouvrage ouvre le champ de la recherche universitaire à un domaine inédit, la littérature conjecturale d’expression française des années 1880 à 1950.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score0.681

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.010
Scholarly communication0.0060.003
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0130.001

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 head0.012
GPT teacher head0.258
Teacher spread0.246 · 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.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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