Support the Troops: Military Obligation, Gender, and the Making of Political Community. By Katharine M. Millar. New York: Oxford University Press, 2022. 304p. $83.00 cloth.
Bibliographic record
Abstract
The military remains one of the most highly trusted institutions in American society.While this level of support can be attributed to specific factors (e.g., public perceptions of competence and professionalism), as identified in the vast literature on civil-military relations, a more affective rationale is also at play.Katharine M. Millar's new book Support the Troops: Military Obligation, Gender, and the Making of Political Community, zeroes in on exactly that.Disagreements about how the military is utilized are commonplace, even healthy in democracies, but there is an enduring and surprisingly robust consensus around supporting the troops.Should we support the troops is a question that is seldom asked but that underlies Millar's riveting and painstaking deconstruction of the ubiquitous "Support the Troops" discourse.Millar boldly suggests that, far from abdicating our duty of care to members of the armed forces, their families, and veterans, we need to carefully scrutinize the promise of belonging, which yellow ribbons bestow upon people.Not supporting the troops is likely to be painted, by Millar's own admission, as a "potentially traitorous" project (p.3).It is not an idea you can just throw out there, given the high emotional stakes involved, and Millar is acutely aware of that.Wisely, she raises that question most directly (and with great sensitivity) only once the reader has been made fully conscious of how pervasive and deeply engrained "Support the Troops" discourses have become.In this book, Millar is adept at uncovering how "Support the Troops" narratives coexist alongside public and official discourses tied to the use of force during the Global War on Terror (GWOT), with an empirical focus on U.S. and UK newspapers, state documents, and military-related non-governmental organizations.The prose can be lengthy and arduous at times, but Millar is always precise and compelling in her analysis.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".