Bibliographic record
Abstract
In Europe in the Early Modern period, women worked an enormous range of jobs and professions. From farmwives who helped plant and harvest crops to fishmongers who sold their wares in markets to guildswomen who engaged in skilled labor, as well as artists, scholars, midwives, doctors, prostitutes, and servants, women participated in every corner of the economy. This wide participation was evident in all of Europe, east as well as west, despite many local and regional differences in how women labored. But notwithstanding the presence of women in all sectors of the economy, women’s work was not understood or valued in the same way as men’s work. In contrast to male workers, female workers saw their ability to practice certain trades curtailed and their capabilities were often seen as inferior to those of men. Women were paid less than men and their work was often more contingent, despite that fact that many families relied on the income or work of all their members. Nonetheless, despite the patriarchal ideology that sought to limit or undervalue their working contributions, women forged ahead working in all sectors of the economy. They did so in order to not only support themselves and their families, but also as part of their self-conception as productive and contributing members of their communities. This article provides sources to support this understanding of the vast range of female economic activity in Europe in the Early Modern period. While women participated broadly in the labor market, it cannot be denied that the pay, professions, and status they enjoyed from those activities were shaped by the assumptions of patriarchy. In her 2008 work Women and Gender in Early Modern Europe, Merry Wiesner notes that “the gender of the worker, not the work itself or its location, marked the difference between what were considered domestic tasks and what was considered production” (p. 104); we can add, the conditions of work and pay hinged upon gendered definitions. For example, one of the most prestigious and lucrative sectors of the economy were skilled trades, often controlled by guilds, especially in France, Germany, the Low Countries, and Italy; English guilds had little real influence by the Early Modern period, but the trades they had controlled remained high-status ones that tried to admit few women. Nonetheless, women found ways to work in skilled trades, regardless of how they were organized. Likewise, other professions marked by high levels of education, pay, and status, such as the law, medicine, academia, and the fine arts, created bars to women joining their ranks, despite the presence of a handful of path-breaking female practitioners. Globally, women were found in greater numbers in less skilled and less lucrative jobs.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.024 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".