Literary Friction: poetics at the operational level of war
Bibliographic record
Abstract
This dissertation explores an intersection between literary studies and war studies, approaching literature as a critical medium that can enhance the conceptualization of war as an organizational process directed towards political and strategic ends. This work of scholarship argues that literature provides unique terms for examining war as a complex interpretive structure, and enumerates historical examples of literary practice as a medium for ideational and transformative activity in military domains. Through this lens, the dissertation explicates the literary aspects of the philosophy of BGen. (ret) Shimon Naveh as it is articulated in his writings on “Systemic Operational Design” (SOD) and operational art. It explores Naveh’s influence on professional military education (PME) in the Israel Defense Force and the legacy of his thinking through the writings of the “Naveh school”, which includes Dr. Ofra Graicer and BGen. (ret) Gal Hirsch, alongside a few others. It highlights how the Naveh school engaged with advanced literary and philosophical texts drawn from a broad corpus of modernist and postmodern literary and philosophical production, including TE Lawrence, John Boyd, Paul Virilio, Gilles Deleuze and Felix Guattari, Hayden White and Bernard Tschumi. By mapping some intellectual spaces where literature has been enlisted in sophisticating military knowledge and activity, this dissertation seeks to broaden the conceptual repertoire of military and security-focused scholarship, offering insights into the ways literary practice has been incorporated in the conceptualization of warfare and strategy in defence organizations and parallel fields of research which support defence organizations. Ultimately, this work seeks to understand the interplay between literary forms and the logics of warfare, pushing the boundaries of how literature is conceptualized within military-academic spaces, while challenging the terms on which war is conceptualized in humanities scholarship.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.014 | 0.068 |
| Scholarly communication | 0.022 | 0.015 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".