Bibliographic record
Abstract
Abstract A scene from Henry Fielding’s Amelia encapsulates the book’s main themes. Fielding depicts a private soldier manhandling a small civilian boy, rousing the ire of his sergeant and the boy’s parents and reinforcing the notion that children need to be protected from war. The very young commanding officer’s support for the soldier reflects contemporary perceptions that juveniles made poor military leaders. On the other hand, the sergeant’s compassion for the boy illustrates the argument of several chapters that children were valuable tools in highlighting warrior sensibility. Children were not only passive objects, however; Childhood and War in Eighteenth-Century Britain has highlighted how their actions and choices affected campaign dynamics. It is also important to recognize their roles in encouraging veterans to tell their stories and sharing their own memories of their wartime childhoods later in life. Historians have not recognized the significance of the child’s gaze in this way, but many contemporary soldiers shared James Anton’s delight in recounting his adventures to starry-eyed youngsters who would “think him a great man.” Children’s admiration for warriors and their desire to preserve their memory has been largely hidden from history. Bringing it to light not only broadens our understanding of childhood, it also deepens our knowledge of the eighteenth-century wars.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.345 | 0.143 |
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".