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Record W3173922888

Savagery and the Heart of Darkness in William Golding’s Lord of the Flies

2012· article· en· W3173922888 on OpenAlexvenueno aff
Afaf Ahmed Hasan Al-Saidi

Bibliographic record

VenueStudies in literature and language · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsInstinctHumanityCivilizationBattleAction (physics)Spanish Civil WarLiteratureWorld War IIPhilosophyHistoryArtAncient historyTheologyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

William Golding’s first-hand experience of battle-line action during World War II “was to shock him into questioning the horror of war. These experiences inform his writing; he was appalled at what human beings can do to one another, in terms of the wartime atrocities…and in their being innately evil” (Foster,7) Two important elements of Golding’s life and experience are powerfully reflected in Lord of the Flies – his pessimism after the Second World War and his insight- as a schoolmaster into the way children behave and function; these two elements from the focus of examination in this paper. What happens when boys are left to their own devices? Golding implies a radical less optimistic view of human nature and civilization. More explicitly, he uses a Pacific island to symbolize the condition of humanity. “Having clinically insulated life on the island from the world and thus contrived a microcosm, he magnifies and inspect it. By this method he examines the problems of how to maintain moderate liberal values and to pursue dis tant ends against pressure from extremis ts and against the lower instincts.” (spark notes.com) Keywords : Tropical island; Children; Beast; Heart of darkness; Savagery

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.410
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.267
Teacher spread0.252 · 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.

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

Citations5
Published2012
Admission routes1
Has abstractyes

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