Men, Women and an Integrated History of the Russian Revolutionary Movement
Bibliographic record
Abstract
Abstract Since its emergence as a discipline in the 1960s, women’s history has had a profound effect on the study of the past. Scholarship on women’s experiences of and contributions to the Russian revolutionary movement has increased exponentially since the publication of a number of biographies of Aleksandra Kollontai in the 1970s and 1980s and a comprehensive picture has emerged of women’s involvement in all the major revolutionary parties, as leading figures as well as rank and file activists. Despite this wealth of historical discovery, remarkably little has found its way into so‐called ‘general’ histories of the revolution. An integrated history, which is the ultimate aim of women’s history, has yet to be produced for the Russian revolutionary movement, even though recent prosopographical studies of revolutionary women have made clear the numerous ways in which men and women cooperated and interacted on a daily basis in the underground. This article explores the nature of and reasons for this failure, makes a case for why incorporating women’s experiences into the grand narrative of the Russian revolution is important and discusses how this might be achieved.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".