Między Wschodem a Zachodem (pisarze czwartej fali emigracji rosyjskiej)
Bibliographic record
Abstract
Between the East and the West (Writers of the Fourth Wave of Russian Emigration) This article attempts to define the phenomenon of the fourth wave of Russian emigration in relation to writers leaving their homeland after the symbolic collapse of the USSR, or who are descendants of representatives of the third wave. The characteristics of contemporary emigration that differ from previous waves of refugees and the reasons for leaving their homeland are indicated here. The destinations of emigrants (USA, Canada, Switzerland, Israel) that shape the specifics of the mental landscape of the newcomers, the barriers, the borders that they have to overcome in order to establish good relations with the citizens of their host countries are also included. Indeed, the aim of multiculturalism is not to tear down walls, but to build bridges. In this respect, dialogue and the associated language as a fundamental distinctive feature of culture that determines the identity of each person is of paramount importance. The current of post-memory, autobiographical and memoir literature, promoted by many emigrants, is linked to identity and its recovery. As far as young emigrants are concerned, they have to live in a global village, in a specific uniformity introduced by the 21st century, which makes mobility one of the most important values.
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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 | 0.001 |
| 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 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".