Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Of every 6,000 soldiers deployed, one publishes an autobiographical book about their experiences shortly after the war. Military memoirs are therefore an inescapable consequence of deployments. How should defence organizations react to these soldier-authors: should they be encouraged, discouraged, or ignored? A substantiated answer to that question is given in this article by providing a profile of all writers of military Afghanistan memoirs from seven countries (the US, the UK, Germany, Canada, Australia, Belgium and the Netherlands) and the kind of plots they write. A small majority write positive plots. The negative ones specifically deal with disillusionment about the care the defence organization or society at large provided, and experiences with Post-Traumatic Stress Disorder (PTSD). It is interesting that it proves to be possible to predict whether a writer will write a positive or a negative plot based on the type of work they do and whether they still work for the defence organization. Military organizations interested in getting positive books published are advised to particularly encourage writing by individually deployed personnel who work in combat support positions and are on active service.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it