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Record W4401037897 · doi:10.1111/basr.12362

Rethinking the relation between human and nature: Insights from science fiction

2024· article· en· W4401037897 on OpenAlexafffund
Corinne Gendron, René Audet

Bibliographic record

VenueBusiness and Society Review · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpace Science and Extraterrestrial Life
Canadian institutionsUniversité du Québec à Montréal
FundersFonds de Recherche du Québec-Société et Culture
KeywordsFlourishingVisionSociologyMovie theaterRelation (database)Futures contractPhenomenonEpistemologyDialog boxOrder (exchange)Science studiesFutures studiesSocial scienceAestheticsPsychologySocial psychologyComputer scienceLiteratureArtPhilosophyEconomics

Abstract

fetched live from OpenAlex

Abstract Facing the accumulation of data that suggest near‐future dramatic changes in our way of life, current visions of transition are anchored in an incremental paradigm that excludes radical change. Using science fiction literature and cinema, this article aims to build such drastic change hypotheses and explore the political–ecological features of future societies emerging from a rupture phenomenon. These post‐ecological societies need to be imagined and analyzed in order to better prepare for eventual dramatic changes and to engage in prospective exercises that contemplate the possibility of flourishing for all in the future. Our work builds on the idea that other forms of knowledge, such as artistic and creative insights produced by science fiction literature and cinema, are promising sources of imagination and must be engaged in a dialog with sociology and other social sciences in order to develop hypotheses of possible futures. The paper introduces six such hypotheses called “scenarios” that were induced from the systematic study of a body of work in classical science fiction production.

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)0.009
metaresearch head score (Gemma)0.021
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.998
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.004
Science and technology studies0.0020.015
Scholarly communication0.0050.007
Open science0.0010.002
Research integrity0.0020.002
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 head0.027
GPT teacher head0.299
Teacher spread0.271 · 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 designTheoretical or conceptual
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
Published2024
Admission routes2
Has abstractyes

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