Bibliographic record
Abstract
Abstract In the Great War, home front schemes in support of wartime causes included the making and transportation of what were called smellies: homemade tokens and commercial gifts that invoked supposedly traditional British scents. For volunteers, this entailed the collection and distribution of homemade lavender and verbena bags as an allegedly effective—and practical—means of aiding those injured at the front. For others, like commercial perfumers, this meant the production of scented commodities like lavender water and eau de Cologne for transport to troops overseas. In both cases, supporters mobilized the symbolic power of perfumed items to promote a fictitious version of rural, white, English life that could allegedly be resumed after the conflict. These campaigns obscured the social, racial, gendered, and material realities of war. What resulted was a profoundly limited definition of British smells and, by extension, their idealized British recipients: white, English-born servicemen from across classes. While perfumed gifts were designed to comfort these select recipients and bring a sense of order to the front, accounts of gifts’ production and reception ultimately reveal fractures—and failures—in the deployment of national smells to order the disordered smellscapes of war.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.026 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".