Rupture and Call: Famine Encounters from Contemporary Irish and Ukrainian Women in the Arts
Bibliographic record
Abstract
In this paper, the authors examine artistic engagement with famine memory by six women artists working in the Irish and Ukrainian contexts: Alanna O’Kelly, Paula Meehan, Mary McIntyre, Oksana Zabuzhko, Nataliia Vorozhbyt, and Lydia Bodnar-Balahutrak. Representing famine in artistic form is mired in ethical challenges. When interpreted at the level of national narratives, such histories can become identities and form a part of the collective ethos. Work by women artists is critically positioned to challenge the strong association between the feminine and the nation found in nationalistic discourses in both Ireland and Ukraine. The artists examined here work across genre and media, yet all eschew stereotypical imagery and prescribed vocabulary for representing famine, thus engaging in the complexities such representation offers. Framing their analysis with Bracha Ettinger’s concept of aesthetic wit(h)nessing, the authors find in the work of contemporary female artists in Ireland and Ukraine opportunities to encounter and grapple with famine memory without immediate recourse to commemoration or resolution. It is thus in the work of women artists today that one finds both a rupture and a call: a rupture to representing famine memory in modes that promote ownership and invite appropriation, and a call to consider what practices, rituals, and acts of wit(h)nessing have sustained life and remembered the dead after famine.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.025 | 0.023 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.005 |
| 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".