Bibliographic record
Abstract
In the paper, the author has analysed the imaginative tools that function in Witold Pilecki’s “Witold’s Report”. First, the figures based on the concept of “beast” and semantically related to it ‘flock of sheep’, ‘herd of sheep’, ‘cow’, ‘beastie’, ‘guinea pig’ and others have been spotlighted. The animals that with the help of appropriate poetic means are predicted to the person who is in the mound of the circumstances of the concentration camp have been outlined. Second, an exemplary paradigm based on the concepts of ‘earth’ and ‘hell’ has been analysed. What happens in the camp is called hell (eg, hell on earth, the world of hell, hell scenes, etc.), and what happens outside the camp is called earth. These images are determined by the realm of religion; the author’s picture of the world, however, is not complete as it lacks a third component — the heavens, the paradise. Instead, there is something like a reality - smoke burning in crematoriums rising into the sky. At the end of the paper, the metaphors observed in Pilecki’s prison language have been spotlighted. The semantics of such metaphorical lexemes and phrases as Muslim is ‘a prisoner who runs away from exhaustion’; sick tourists - ‘typhoid patients taken to Brzezinka crematorium’; disinfestation of life - ‘release the hospital from the sick by killing them’; Canada - ‘valuables and money left over by gas strangled Jews enriched by the Germans and some prisoners’ and others — have been analysed. As long as one lives, he creates metaphors, even in the macabre world of the death camp. “Witold’s Report” is a valuable testimony of Witold Pilecki about the Auschwitz concentration camp, where people who were poisoned by the Nazi ideology found traits that were “worse than worse than animals” and prisoners often looked like animals.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".