Bibliographic record
Abstract
WINNER, JAVIER COY BIENNIAL RESEARCH AWARD, BEST MONOGRAPH Offers a fascinating window into how the fraught politics of apology in the East Asian region have been figured in anglophone literary fiction. The Pacific War, 1941-1945, was fought across the world’s largest ocean and left a lasting imprint on anglophone literary history. However, studies of that imprint or of individual authors have focused on American literature without drawing connections to parallel traditions elsewhere. Beyond Hostile Islands contributes to ongoing efforts by Australasian scholars to place their national cultures in conversation with those of the United States, particularly regarding studies of the ideologies that legitimize warfare. Consecutively, the book examines five of the most significant historical and thematic areas associated with the war: island combat, economic competition, internment, imprisonment, and the atomic bombing of Hiroshima and Nagasaki. Throughout, the central issue pivots around the question of how or whether at all New Zealand fiction writing differs from that of the United States. Can a sense of islandness, the ‘tyranny of distance,’ Māori cultural heritage, or the political legacies of the nuclear-free movement provide grounds for distinctive authorial insights? As an opening gambit, Beyond Hostile Islands puts forward the term ‘ideological coproduction’ to describe how a territorially and demographically more minor national culture may accede to the essentials of a given ideology while differing in aspects that reflect historical and provincial dimensions that are important to it. Appropriately, the literary texts under examination are set in various locales, including Japan, the Solomon Islands, New Zealand, New Mexico, Ontario, and the Marshall Islands. The book concludes in a deliberately open-ended pose, with the full expectation that literary writing on the Pacific War will grow in range and richness, aided by the growth of Pacific Studies as a research area.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.072 | 0.023 |
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".