The sun doesn't shine so brightly any more
Bibliographic record
Abstract
"Gisela Feldman was born in Berlin in 1923. Gisela recounts the Nazi rise to power and witnessing a terrifying night when her father was taken away by the Nazis. After Kristallnacht, Gisela's mother knew they had to leave Germany. She managed to arrange visas for Cuba and passage there on a liner, the SS St Louis, for herself and her two daughters. However, Cuba, the USA and Canada all refused entry to the ship, and they were eventually given permission to come to England via Antwerp. After working as an au pair and a machinist in London, Gisela went on to have a long career as a teacher. She married Oscar and they had three children. She moved to Manchester in 1995 to be near her son and grandchildren. Gisela's book is part of the My Voice book collection, a stand-alone project of The Fed, the leading Jewish social care charity in Manchester, dedicated to preserving the life stories of Holocaust survivors and refugees from Nazi persecution who settled in the UK. The oral history, which is recorded and transcribed, captures their entire lives from before, during and after the war years. The books are written in the words of the survivor so that future generations can always hear their voice. The My Voice book collection is a valuable resource for Holocaust awareness and education."
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.035 | 0.010 |
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".