Słowo i obraz – teksty i związane z nimi motywy ikoniczne na nagrobkach kobiet na cmentarzach żydowskich na historycznych obszarach Rzeczypospolitej
Bibliographic record
Abstract
Word and Image: Texts and Related Iconic Motifs on Women’s Gravestones in Jewish Cemeteries in the Historical Areas of The Republic of Poland The research material in the article covers the period from the earliest gravestones from the fourteenth century to contemporary ones of the twenty-first century. Among iconic motifs taken into account are those which are specific for women’s gravestones, and from texts in inscriptions—those corresponding to artistic motifs. The aims of this study are the following: to distinguish thematic groups, determine the range of iconic motifs used and the chronology and frequency of their occurrence, as well as to juxtapose them with normative content from religious writings of Judaism and with rites and customs. The following conclusions emerge from the research: In the early period (until the fourth quarter of the eighteenth century), there was no differentiation on tombstones between separate motifs ascribed to men (except for the Kohanim and Levites) and separate motifs ascribed to women. Among the common motifs, the bird motif dominated on women’s gravestones, while the crown motif acquired its specific character. In the fourth quarter of the eighteenth century, the motif of a candlestick appeared on women’s gravestones; it spread very quickly and became a visual identification feature. In the nineteenth century, with the introduction of vanitas motifs on gravestones, they began to be used on women’s gravestones. The connection of motifs with the names of the deceased is also noticeable (e.g. Feigl–bird, Rachel–fairy, Royza–rose, or scenes related to biblical namesakes). The contents of women’s epitaphs presented as praise or description of virtues largely concern traditional female duties toward the home, husband, and children. Women’s gravestones contain no attributes or references to the study of Torah and scholarship, or else to activities in the public sphere—to professions, both religious and later secular—which obviously results from the position and role of women in the patriarchal community. Such information does not appear until the interwar period on the tombstones of women from families assimilated into the surrounding culture which is also evidenced by non-traditional tombstone forms and inscriptions in non-Jewish languages.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".