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Record W7071275649

Reproducción y violencia sistémica en la ciencia ficción británica contemporánea: Intrusion (2012), The Growing Season (2017) y The Birth of Love (2010)

2024· article· es· W7071275649 on OpenAlexaboutno aff

Bibliographic record

VenueZaguan (University of Zaragoza Repository) · 2024
Typearticle
Languagees
FieldArts and Humanities
TopicUtopian, Dystopian, and Speculative Fiction
Canadian institutionsnot available
Fundersnot available
KeywordsIntrusionHuman sexualityBirth controlNova scotiaAbortionReproduction
DOInot available

Abstract

fetched live from OpenAlex

Históricamente en las sociedades patriarcales, las mujeres han sido excluidas de sus procesos sexuales y reproductivos, desde los orígenes de las prácticas biomédicas y anatómicas hasta el uso de las tecnologías reproductivas más avanzadas. En este artículo se analizarán tres novelas británicas contemporáneas de ciencia ficción y la representación de la exclusión de la mujer en tres campos principales de la sexualidad: el control de la sexualidad femenina y la reproducción en Intrusion (2012), de Ken MacLeod; la gestación en The Growing Season (2017), de Helen Sedwick, y el parto en The Birth of Love (2010), de Joanna Kavenna. Historically, in patriarchal societies women have been excluded from their sexual and reproductive processes, from the origins of biomedical and anatomical practices to the use of the latest reproductive technologies. In this article three contemporary British science fiction novels will be analysed, as well as the representation of the exclusion of women in three main fields of sexuality: the control of female sexuality and reproduction in Ken MacLeod’s Intrusion (2012); gestation in Helen Sedwick’s The Growing Season (2017) and childbirth in Joanna Kavenna’s The Birth of Love (2010).

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.170
Threshold uncertainty score0.338

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0130.039
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.000

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 head0.013
GPT teacher head0.204
Teacher spread0.192 · 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 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
Published2024
Admission routes1
Has abstractyes

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