Austro-Hungarian Women’s Activism from the Southern “Periphery” Across Ethnic Lines
Bibliographic record
Abstract
Through the examples of Adél Nemessányi, Milica Tomić, Jelica Belović-Bernadžikovska, and Nafija Sarajlić, four women activists, public workers, and writers from the southern “peripheries” of Austria-Hungary who belonged to different ethnic groups, this paper examines the complex local, regional, and trans-regional aspects of women’s awakening and organizing in the Dual Monarchy. While none of these four women belonged to any associations that demanded political rights for women, their public work and activism, which took multiple forms, greatly contributed to the improvement of women’s public image, education, and social status in their own time, leaving an imprint on future generations. Through both the personal and professional lives of these remarkable women, we can discern connections that transgress ethnic, regional, and national boundaries and also reflect international developments in the fight for women’s rights. This ethnically varied sample of exceptionally educated women pioneers from parts of the Dual Monarchy that would later become Yugoslavia demonstrates what women were able to accomplish despite an overall conservative social environment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".