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Lingua Cosmica

2018· book· en· W4248806389 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Illinois Press eBooks · 2018
Typebook
Languageen
FieldArts and Humanities
TopicUtopian, Dystopian, and Speculative Fiction
Canadian institutionsnot available
Fundersnot available
KeywordsLingua francaHistoryChinaFrenchLiteratureMedia studiesSociologyClassicsHumanitiesArt historyArt

Abstract

fetched live from OpenAlex

<italic>Lingua Cosmica: Science Fiction from around the World</italic> consists of eleven scholarly essays on contemporary authors (born 1950 or later) of science fiction who publish in languages other than English, or who publish from the English-speaking “periphery”: i.e., outside the United States, the United Kingdom, and Anglophone Canada. Each essay examines one author, making a case for their importance internationally and contextualizing their work within the science-fictional traditions of their own culture and those of the genre globally (themes, tropes, tendencies, subgenres, etc.). Each also offers an in-depth analysis of a major work or works. The book thus identifies major contemporary authors of science fiction outside the “center” of the English-speaking world and presents them to students and scholars in the Anglophone world. The scholars respond to questions such as: Who are these authors, and why are they important? What innovative thematic material or formal elements do they offer? What unique elements from their culture do they bring to the genre? How do they dialogue with the history of the genre, and how do they fit into the contemporary SF scene? The authors studied are Angélica Gorodischer from Argentina, Yves Meynard and Jean-Louis Trudel writing collaboratively as Laurent McAllister (Francophone Canada), Liu Cixin (China), Daína Chaviano (Cuba), Johanna Sinisalo (Finland), Jean-Claude Dunyach (France), Andreas Eschbach (Germany), Sakyo Komatsu (Japan), Olatunde Osunsanmi (Nigerian American), Jacek Dukaj (Poland), and Arkady Strugatsky and Boris Strugatsky (Russia/USSR).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.944
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.038
GPT teacher head0.192
Teacher spread0.154 · 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 teacher head, not a consensus.

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
Published2018
Admission routes1
Has abstractyes

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