Women, business and finance in nineteenth-century Europe : rethinking separate spheres
Bibliographic record
Abstract
Contents 1. Introduction Beatrice Craig, Robert Beachy and Alastair Owens 2. 'Making some provision for the contingencies to which their sex is particularly liable': Women and Investment in early nineteenth-century England Alastair Owens (Queen Mary, University of London) 3. 'The Silent Partners': Women, capital and the development of the financial system in nineteenth century Sweden Tom Petersson (Uppsala University, Sweden) 4. 'Where have all the businesswomen gone?' Images and reality in the life of nineteenth-century middle-class women in northern France Beatrice Craig (University of Ottawa, Canada) 5. 'Profit and Propriety': Sophie Henschel and gender management in the German locomotive industry Robert Beachy (Goucher College, USA) 6. Artisan women and management in nineteenth-century Barcelona Juanjo Romero-Marin 7. Women and Publishing in Nineteenth Century Spain Gloria Espigado, University of Cadiz, Spain 8. Businesswomen in Austria Irene Bandhauer-Schffmann (University of Klagenfurt, Austria) 9. Belgium's Tradeswomen Valrie Piette (University of Brussels, Belgium) 10. Limited Opportunities? Female retailing in nineteenth-century Sweden Tom Ericsson (Umea University, Sweden) 11. Retailing, respectability and the independent woman in nineteenth century London Alison C. Kay (Research Fellow, Department of Geography, King's College London) 12. Hidden Professions? Female 'placers' of domestic servants in nineteenth-century Dutch cities Marlou Schrover (Leiden University, The Netherlands) 13. The business of sex: Evaluating prostitution in the German port city of Hamburg Julia Bruggeman (De Pauw University, USA)
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.024 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".