Polish Literary Reckoning of the Post-WWII Population Resettlement: the Lens of “Tender Narrator”
Bibliographic record
Abstract
This article investigates two literary texts, House of Day, House of Night (2002) by Olga Tokarczuk and Piaskowa Góra [Sand Mountain] (2009) by Joanna Bator and how they overcome the divisive and politicized narration of the post-WWII population expulsions and resettlement in Poland. The article argues that by employing the “tender narrator,” (Tokarczuk, 2019) e.g. directing readers’ attention to the former German items of everyday use and their stories, the writers create a more empathetic version of this period of history, thus recovering the memories of the, largely silenced, Polish and German experiences of displacement. Adopting postcolonial approaches, the article draws from affect theories and studies of how displaced populations relate emotionally to the changing material environment (Svašek, 2012) to examine the attitudes and emotions of the Poles dealing with the objects, landscape and property of the German deportees. These texts raise important questions about the foundations of the communities in the Polish-German borderlands, and their wider implications for Polish-German relations.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".