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Record W4224216115 · doi:10.33137/qi.v42i1.38478

Climate Change: Eco-Dystopia in Antonio Scurati’s La seconda mezzanotte

2022· article· en· W4224216115 on OpenAlexvenueno aff
Anna Chiafele

Bibliographic record

VenueQuaderni d italianistica · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGothic Literature and Media Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMidnightDystopiaNarrativeComedyClimate changeTopos theoryHistoryArtHumanitiesGeographyLiterature

Abstract

fetched live from OpenAlex

This article offers an examination of the novel La seconda mezzanotte (2011) by Antonio Scurati. Classified by the author as a catastrophist sci-fi novel, this work is here defined and analyzed as one of the very first Italian examples of climate fiction (cli-fi), a narrative form especially popular in North America, closely related to anthropogenic climate change. The essay discusses some of the topoi that characterize Anglo-Saxon cli-fi, which are clearly present in The Second Midnight. Such recurring motifs will also be discussed, in particular, by highlighting some of the rhetorical tools adopted by Scurati, such as, for example, the effect of estrangement. Through such effects, the reader is spurred to adopt an uncomfortable, “oblique” and unusual gaze. This study highlights Antonio Scurati’s skill and originality in dealing with the causes and global effects of climate change. The author succeeds in making the reader perceive the spatial and temporal magnitude of global warming, which in 2072 Venice materializes dramatically in a Big Wave. The Second Midnight is a human comedy that expands across centuries and continents while narrating the events of a few men living in Nova Venezia in a specific year, 2092. Distant spaces, remote times, human and non-human corporealities converge in a new Venice, which is a piece of a hologram narrating other people’s stories.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.970
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.000

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 head0.026
GPT teacher head0.302
Teacher spread0.277 · 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
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
Published2022
Admission routes1
Has abstractyes

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