Wspólnoty pamięci Hołodomoru w USA i Kanadzie w latach 50.-80. XX wieku
Bibliographic record
Abstract
Communities of Memory of the Holodomor in the USA and Canada in the 1950s-80s The main goal of this article is to show how the Ukrainian community in North America, thanks to cultivating the memory of a marginal event from the point of view of American history, managed to appear in the social life of the USA and Canada. Here I use the concept of ‘community of memory’ to emphasize those Ukrainian communities in the USA and Canada that are of utmost importance in the commemoration of Holodomor. They also managed to retain this event’s memory in many other competing memories, dabbling in the memory of their identity as American Ukrainian. Therefore, in the following sections of the article, I will attempt to answer why it was the diaspora that undertook a tremendous effort to commemorate Holodomor’s victims and the course of that process for years. Finally, I employ critical analysis of media discourses. Moreover, I will consider the Holodomor generation’s role in cultivating that memory and emergence of the ‘communities of memory’.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".