Bibliographic record
Abstract
The role of the Women’s Land Army (WLA) in the agricultural history of the First World War has often been overlooked due to the seemingly minor role played by the organisation in maintaining domestic food production between its formation in January 1917 and its demobilisation in October 1919. The WLA, however, marked the first time that a group of women came together in a national organisation for farm work. The creation of the WLA was part of a broader effort to mobilise a domestic force of women workers, but with the specific task of replacing the male agricultural labourers who had enlisted or who had been conscripted into Britain’s armed forces. This study argues that although farm work became an imperative patriotic act, valued not just for the food produced, but also through the symbolic act of tending the land, organisers like Meriel Talbot (the Director of the Women’s Branch in charge of the WLA) and Edith Lyttelton (Deputy Director) did not envision the organisation simply in patriotic terms. The WLA was formed to help solve the real problem of the dwindling agricultural labour supply, but organisers believed that a national organisation would help convince farmers, potential recruits, and the public of the valuable role women could play in agriculture, not only in wartime, but as a viable employment opportunity beyond the years of the conflict.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.279 | 0.103 |
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".