Gender and Modernity in Central Europe: The Austro-Hungarian Monarchy and its Legacy
Bibliographic record
Abstract
GENDER AND MODERNITY IN CENTRAL EUROPE: THE AUSTRO-HUNGARIAN MONARCHY AND ITS LEGACY Agatha Schwartz, Ed. Ottawa: University of Ottawa Press, 2010 Memory of the fin-de-siecle Austro-Hungarian monarchy is usually male-dominated and connected to famous thinkers such as Sigmund Freud, the painter Gustav Klimt or the writer Robert Musil. The reader of the volume Gender and Modernity in Central Europe: The Austro-Hungarian Monarchy and its Legacy recognizes very quickly that the late Habsburg monarchy was much more than Klimt and Freud. Life in the empire was characterized by an astonishing plurality and innovation of ideas and discourses that were produced in an atmosphere full of contradictions, as the editor of the volume Agatha Schwartz states in her introduction. Schwartz claims that the contributions in this volume address the necessity for a creative discussion between representatives of disciplines, regions and countries on gender and modernity. The multidisciplinarity of this volume is indeed one of its strengths. It contains contributions from the fields of history, art history, sociology, literary studies, and psychology. Furthermore, this volume excels in merging two dissonant discourses into one transatlantic narrative. This collection proves that research on the Habsburg Empire is particularly rewarding because of its high transnational potential. Helga Thorson's article on Grete Meisel-Hess, an under- researched feminist Austrian writer, takes up the transnational aspect and shows how ethnic and sexual tensions were intertwined in the early twentieth-century and played a significant role in the formation of female identity. In another essay, Susan Ingram highlights an interesting connection between Czech nationalism and feminism which opposed traditional constructions of empire and gender roles within the Habsburgian presence at the 1893 Chicago Columbian Exhibition. Moreover, research on developments on a local level makes a valuable addition to this volume. Michaela Raggam-Blesch looks at the biographies of three pioneering female Jewish students at the University of Vienna who were facing discrimination in a predominantly male setting. These students, despite their marginalization, managed to integrate into university, but spaces of female agency mostly remained private, as Alison Rose shows in her contribution on the salons of Jewish Women. According to the author, these salons played an important role in the development of modernity and enabled women to operate as leaders and still maintain their bourgeois femininity. …
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".