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Record W2956115512 · doi:10.29173/jjs12s

House of Cards

2018· article· en· W2956115512 on OpenAlexvenueno aff
Joli Hamilton

Bibliographic record

VenueJournal of Jungian Scholarly Studies · 2018
Typearticle
Languageen
FieldPsychology
TopicJungian Analytical Psychology
Canadian institutionsnot available
Fundersnot available
KeywordsPsycheFreudian slipShadow (psychology)PsychoanalysisUnconscious mindConsciousnessPower (physics)InnocenceAestheticsFantasyLiteraturePhilosophyArtPsychologyEpistemology

Abstract

fetched live from OpenAlex

This essay turns a depth-psychological lens upon the drug abuse, sexual manipulation, and murder scenes in the American television rendition of House of Cards. The Underwoods, who are obsessed with power, yet strangely enticing, invite the viewer to upend their moralistic perspective challenging notions of innocence and evil. By applying post-Freudian Lacan’s Phallus theory, the unconscious and persistent desire for power in some individuals is explored. Then, in a move toward understanding why audiences flock to such grotesque imagery, post-Jungian Moore’s notion of dark eros is extended to argue for the necessity of accepting the sadistic aspect of psyche. The notion of libertine consciousness is used to illuminate why the darkness draws us in even as it is repulsive and suggest the cautious, reflective digestion of these grotesque images as a creative action for those challenged by current political darkness. Bringing Lacan and Moore into dialogue, it is suggested that sexually toned darkness may necessarily balance the pull toward light aspects of psyche. Through close reading, intense scenes are reimagined as more than just Jungian shadow material. They also illustrate the sacrifice of innocence required as one attempts to increase consciousness.

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)0.002
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.630
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.076
GPT teacher head0.406
Teacher spread0.329 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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