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Record W1522674822 · doi:10.29173/jjs74s

Writing about War:

2007· article· en· W1522674822 on OpenAlexvenueno aff
Susan Rowland

Bibliographic record

VenueJournal of Jungian Scholarly Studies · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicViolence, Religion, and Philosophy
Canadian institutionsnot available
Fundersnot available
KeywordsNothingTragedy (event)LiteraturePatriarchyComedyPsychicConsciousnessEPICHistorySpanish Civil WarPhilosophyArtPsychoanalysisSociologyPsychologyGender studies

Abstract

fetched live from OpenAlex

Arguably, in a time of war literature, and indeed all writing, is saturated with deep psychic responses to conflict. So that not only in literary genres such as epic and tragedy, but also in the novel and comedy, can writing about war be discerned. C.G. Jung, Shakespeare and Lindsay Clarke are fundamentally writers of war who share allied literary strategies. Moreover, they diagnose similar origins to the malaise of a culture tending to war in the neglect of aspects of the feminine that patriarchy prefers to ignore. In repressing or evading the dark feminine, cultures as dissimilar as ancient Greece, the 21st century, Shakespeare's England and Jung's Europe prevent the healing energies of the conjunctio of masculine and feminine from stabilising an increasingly fragile consciousness. In the Troy novels of Clarke, Answer to Job by Jung and Much Ado About Nothing by Shakespeare, some attempt at spiritual nourishment is made through the writing.

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)0.004
metaresearch head score (Gemma)0.011
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: Other · Consensus signal: Other
Teacher disagreement score0.016
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.014
Scholarly communication0.0130.009
Open science0.0010.008
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0160.005

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 head0.055
GPT teacher head0.299
Teacher spread0.244 · 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
GenreOther

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
Published2007
Admission routes1
Has abstractyes

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