Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A fifth of West Germany's post-1945 population consisted of ethnic German refugees expelled from Eastern Europe, a quarter of whom came from Silesia. As the richest territory lost inside Germany's interwar borders, Silesia was a leading objective for territorial revisionists, many of whom were themselves expellees. The Lost German East examines how and why millions of Silesian expellees came to terms with the loss of their homeland. Applying theories of memory and nostalgia, as well as recent studies on ethnic cleansing, Andrew Demshuk shows how, over time, most expellees came to recognize that the idealized world they mourned no longer existed. Revising the traditional view that most of those expelled sought a restoration of prewar borders so they could return to the east, Demshuk offers a new answer to the question of why, after decades of violent upheaval, peace and stability took root in West Germany during the tense early years of the Cold War.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it