The Figure of the Migrant and a Lithuanian Attempt to Escape from Herself
Bibliographic record
Abstract
For those engaged in the visual arts, the notion of the border is not just a physical reality imposed on the landscape by historical circumstances and political forces; it is also the subject of imagination, representation and visualization. For European artists, how migration, refugees and new ethnic and religious communities continue to develop is of particular importance. This essay examines the relativities between the so-called re-territorialization of borders and their materialized visual image. In doing so it seeks to reflect the balance between claims of difference and sameness, and also the dynamics that exist between dominant perceptions and self-representations of the refugees themselves. Over the last decade the notion of border has been fixed and consolidated in the artistic consciousness, especially how this phenomenon – barrier, walls or fences – can divide. With the crisis of mass migration in recent years, there has been an accompanying sense of dread, horror, a fear of death and the loss of family. The experience and ideas of the Lithuanian artist, Sigita Maslauskaitė-Mažylienė, is useful because it sheds light on the interconnections between new discourses and art practices, and may help us to better understand how Lithuanian people perceive the process of migration and its accompanying problems and issues.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.018 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".