Blending Postmodernism with Military Design Methodologies: Heresy, Subversion, and other Myths of Organizational Change
Bibliographic record
Abstract
The emergence of postmodern thinking in 21st century military practice, theory, and education is apparent through various international Armed Forces research, debate, and professional development. However, there is yet to exist a single overarching or agreed upon form for a postmodern military methodology, with extensive disagreement over language, form, function, and practical application in war. This essay frames the current debate by proposing an emergent movement termed the ‘postmodern military movement’ that is in conflict with the existing ‘modernist military movement’ well entrenched in most Anglo-Saxon Armed Forces. More significantly, the military appropriation of postmodern social theory invokes subsequent questions of whether the military might forge novel war applications that redefine the larger postmodern movement, or if it will remain untouched. This essay describes the current competing design theories as well as the personal journey of the author as he contributes his own military research and experimentation into the larger military profession for institutional debate and self-reflection.
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 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 | 0.045 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.007 | 0.146 |
| Scholarly communication | 0.018 | 0.019 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".