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
This review article examines Mateusz Świetlicki’s (2023) monograph, Next-Generation Memory and Ukrainian Canadian Children’s Historical Fiction: The Seeds of Memory. The publication opens with the author’s own childhood memories and takes readers on a journey through various periods of Ukrainian Canadian and Ukrainian history as portrayed in children’s historical fiction. Across five chapters, Świetlicki explores the works of Canadian children’s authors who depict Ukrainian emigration to Canada in the late 19th and early 20th centuries, as well as the role of Ukrainian immigrants in settling the prairies. He also considers how these books portray relationships between Ukrainian settlers and Indigenous Peoples, rework narratives about internment camps during World War I, and explore the cultural significance of Ukrainian “seeds of memory,” symbolised by Easter pysanky. Turning to 20th-century Ukrainian history, Świetlicki explores representations of Soviet atrocities, including the Holodomor, along with World War II, the Nazi occupation of Ukraine, and the Holocaust. Throughout his work, he highlights the complexities of these historical events and emphasises the key role of children’s literature in fostering a deeper, more meaningful understanding of the past among young readers.
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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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