Bibliographic record
Abstract
The main character in David Albahari’s novel Bait leaves Serbia and flees to Canada where he tries to start his life anew. The narrator finds himself alone and lonely, sad, troubled and completely estranged from his new surroundings, language, culture and people. The paper will primarily rely on Edward Said (2001) and Svetlana Boym’s (2001) definitions and meanings of exile in which they both recognize loss as its fundamental element. This paper aims to show the complexity of loss following exile and the ways to constructively overcome it. The narrator’s life in the novel is filled with different losses – that of his home country, language, his people, identity and sense of belonging. Despite all the promises of a better life that Canada seems to offer to the novel’s narrator, Albahari portrays him as a man who is suffering and desperately trying to adapt to everything that Canada represents. The paper will focus on how the narrator navigates his alienation and attempts to forge a new identity in a new country whilst enduring the sadness and estrangement of his self-imposed exile. Keywords: Albahari, exile, loss, country, language, estrangement, identity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".