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Record W4415957902 · doi:10.1558/post.33809

‘Imago Dei’ in Sheri S. Tepper’s ‘The Companions’

2025· article· W4415957902 on OpenAlexaff
Stephanie Studzinski

Bibliographic record

VenuePostscripts The Journal of Sacred Texts Cultural Histories and Contemporary Contexts · 2025
Typearticle
Language
FieldArts and Humanities
TopicUtopian, Dystopian, and Speculative Fiction
Canadian institutionsAmbrose University
Fundersnot available
KeywordsHumanityIntellectEmpathyKinshipImagoValue (mathematics)Performative utteranceIntrospection

Abstract

fetched live from OpenAlex

Imago Dei is frequently problematized in speculative fiction (SF) as humanity’s own narcissism symbolized by a rigid adherence to simplistic taxonomic definitions of humanity. Accordingly, nonhuman lifeforms have little value or right to life, creating mass extinctions and ecoapocalypses. American author Sheri S. Tepper challenges this definition through non-terrestrial nonhumans with their own imago Dei beliefs – but with different gods which, in a reversal of roles, leads them to devalue and destroy humanity. Tepper’s oeuvre further satirizes these views by contrasting them with a performative imago Dei wherein nonhuman and hybrid humans are said to be human in that they communicate and display a superior intellect and empathy to that of “humans.” Tepper’s SF offers readers two futures: Humanity redefines itself based on kinship with all Creation and physically changes, making itself in a new image, or humanity rejects change, choosing extinction.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.023
Scholarly communication0.0040.005
Open science0.0010.002
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0040.001

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 head0.028
GPT teacher head0.254
Teacher spread0.226 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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