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Record W2161450581 · doi:10.5539/ells.v2n2p46

‘I Didn’t Raise My Boy To Be a Soldier’ The Impact of War in Eugene O’Neill’s The Sniper

2012· article· en· W2161450581 on OpenAlexvenueno aff
Hana’ Khalief Ghani

Bibliographic record

VenueEnglish Language and Literature Studies · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicPolitics and Conflicts in Afghanistan, Pakistan, and Middle East
Canadian institutionsnot available
Fundersnot available
KeywordsSection (typography)DehumanizationFirst world warWorld War IIHistorySpanish Civil WarMedia studiesLiteratureSociologyPsychologyPolitical scienceLawClassicsAncient historyArtAdvertising

Abstract

fetched live from OpenAlex

Eugene O’Neill is one of the most important American dramatists. He began his writing career at the start of World War I and ended it at the conclusion of the Second. No doubt, the two World Wars profoundly and permanently affected the lives of people all over the world. As his country became increasingly involved in these wars, O’Neill reacted in his own way to the horrors, dehumanization and monstrosity of war experiences. O’Neill’s The Sniper sheds light on the shattering impact of the outbreak of armed conflict on the lives of simple ordinary people-Rougon’s family in this case. Since The Sniper is written in 1915, section one of the present study is devoted to the American participation in World War I, section two to O’Neill’s attitude toward war while the third section deals with the play per se. The study is rounded off with a Conclusion in which the most important findings are stated.

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)0.003
metaresearch head score (Gemma)0.007
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: none
Teacher disagreement score0.047
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0170.011
Scholarly communication0.0050.005
Open science0.0010.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.021
GPT teacher head0.347
Teacher spread0.326 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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