Bibliographic record
Abstract
Becoming My Mother’s Daughter: A Story of Survival and Renewal tells the story of three generations of a Jewish Hungarian family whose fate has been inextricably bound up with the turbulent history of Europe, from the First World War through the Holocaust and the communist takeover after World War II, to the family’s dramatic escape and emmigration to Canada. The emotional centre and narrative voice of the story belong to Eva, an artist, dreamer, and writer trying to work through her complex and deep relationship with her mother, whose portrait she cannot paint until she completes her journey through memory. The core of the book is Eva’s riveting recollection of the last months of World War II in Budapest, seen through a child’s eyes, and is reminiscent in its power of scenes in Joy Kogawa’s Obasan . Exploring the bond between generations of mothers and daughters, the book illustrates the struggle between the need for independence and the search for continuity, the significant impact of childhood on adult life, the reshaping of personality in immigration, the importance of dreams in making us face reality, and the redemptive power of memory. Illustrations by the author throughout the book, some in colour, enhance the story.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".