Rewriting the<i>Reich</i>: German Women Journalists as Transnational Mediators for Germany's Rehabilitation
Bibliographic record
Abstract
Abstract This article looks at the transnational impact of two diaries written by the female German journalists Ruth Andreas-Friedrich and Ursula von Kardorff, whose journals shed light on German wartime experiences, resistance activities, and, to a lesser extent, the press. In the postwar years, both journalists sought to influence (West) Germany's relationship with its former enemies, in particular the United States. In their autobiographical writing, they presented both an image of Germany as a victim of Nazism, as well as an early acknowledgment of German crimes. In this way, they achieved a balanced narrative that received a positive reception from American and German audiences. Though the ways in which Friedrich and Kardorff presented aspects of journalism and everyday life in the Third Reich were not unique, their dual identity as women and journalists underlay their ability to act as “legitimate” mediators for Germany's rehabilitation. Western allied occupation authorities and overseas audiences viewed them, in contrast to men, as largely apolitical because they were women, and as objective witnesses because they were journalists. Through their autobiographical writings, both journalists situated themselves among the predominantly male US and German elites devoted to developing amicable relations between the two countries via soft-power diplomacy.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.016 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".