Visual Fictions and the U.S. Treasury Courtesans: Images of 19th-Century Female Clerks in the Illustrated Press
Bibliographic record
Abstract
During the Civil War, the United States Treasury began hiring female clerks to work within its departments, a decision that would lead to the federal government becoming, according to historian Cindy Sondik Aron, “the first large, sexually integrated, white-collar bureaucracy in America.” By 1864, a congressional committee had already begun looking into accusations that some of the women were mistresses of government officials and that the Treasury Department had been turned into a harem. A second scandal, this time playing out in the press in 1869, renewed the old imagery of the harem. This article looks at how female Treasury clerks were portrayed in the two most popular illustrated weeklies at the time, Frank Leslie’s Illustrated Newspaper and Harper’s Weekly, as well as The Days’ Doings and Harper’s Bazar, and the use of misleading visual tropes that called women’s characters into question. The employment of these pernicious “visual fictions” aided in the creation of stereotypes of working women that continued well into the twentieth century, which, in turn, contributed to the devaluation of white-collar women and their work.
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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 | 0.015 | 0.012 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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 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".