The Anti-War Poetry of Herbert Read: “Kneeshaw Goes to War” as an Example
Bibliographic record
Abstract
This study aims at investigating the nature of the anti-war poetry of the English poet, Sir Herbert Read (1893 -1968). First, it surveys the different styles that the anti-war poets followed in their criticism of war in an attempt to figure out afterwards the characteristics that distinguish Read’s anti-war poetry from other poetry. It then presents the main features of Read’s anti-war poetry. The study moves on to examine its main objective that lies in analyzing Read’s poem “Kneeshaw Goes to War” (1918) as an example of his own anti-war poetry. This thematic study follows a descriptive and analytical method in carrying out its aim. It starts with an introduction about the different modes of war poetry and literature review, develops into a discussion of Read’s attitude towards the poem’s main subject and comes to an end with the main findings in the conclusion. Read was able to use a realistic approach in his criticism of war in his poem “kneeshaw Goes to War”. In his portrayal of the destructiveness of war, he managed to expressionistically convey his sense of despair that the war had generated in the individual’s personal experience with war. The representation of human experience is thus as important as the anti-war theme itself in the poem.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".