Review of Gender and the Modern Research University: The Admission of Women to German Higher Education, 1865-1914
Bibliographic record
Abstract
were top-ranking civil servants who, dissatisfied with the status quo, were eager to change the nature of policy making and administration in higher education.The persuasive tactics that they used succeeded because there was already a changing climate toward the development of a civil society.In the final analysis, there is no single theory that accounts for the Austrian experience.Instead, the successful policy transfer can be attributed to a combination of factors, including the robustness of institutions.The individual chapters in this book are very well written, each providing vivid historical details of the change process it describes.Paradoxically however, this commendable feature detracts from the book's integration and coherence as there is much repetition, particularly across the earlier chapters, in the narration of the historical process of developing the Austrian system.Although the book's stated focus is the accreditation model, this key concept is not defined until mid-way through the book (on page 70), and a full analysis of the policy transfer does not occur until the last two chapters.Despite these shortcomings, the book provides an interesting history of two similar yet different systems of higher education, and the unique ways in which one was inspired by and modelled on the other.It would therefore be of interest to scholars of public policy, as well as to educational administrators and historians.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".