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Record W4386537381 · doi:10.29173/spectrum197

Women, Role Failure, and the Nuclear Family in Stephen King’s The Shining

2023· article· en· W4386537381 on OpenAlexvenueno aff
Kyra McKauffley

Bibliographic record

VenueSpectrum · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGothic Literature and Media Analysis
Canadian institutionsnot available
FundersHumanities Research Center, Rice UniversityRice University
KeywordsWifeNuclear familyHappinessAutonomyPower (physics)DelegationWhite (mutation)Nuclear powerAnxietyNuclear weaponPsychologyAbuse of powerPsychoanalysisSociologyCharacter (mathematics)Gender studiesCriminologySocial psychologyPolitical scienceLawPsychiatryPolitics

Abstract

fetched live from OpenAlex

While Stephen King’s The Shining (1997) features a hotel haunted by ghosts, the main female character Wendy Torrance is much more haunted by her fear of failing to fulfill her gender role within the structure of the traditional, white, American nuclear family. In this paper, I analyze how the fear of being an unsuccessful wife and mother illustrates structural problems within the nuclear family that are detrimental to women. Not only do they produce persistent insecurity and anxiety, but they also reinforce the delegation of power to a sole patriarchal authority figure. The Shining reveals how these issues become especially problematic in situations of abuse. However, it also presents an opportunity for women to escape from both abuse and the fear of role failure: completely abandoning the structure of the nuclear family. Thus, The Shining illuminates inherent flaws within the nuclear family’s roles and suggests that women cannot find autonomy, freedom, or happiness within its confines.

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)0.003
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 score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0140.032
Scholarly communication0.0070.006
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.241
Teacher spread0.231 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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