Vem vittnar för vittnet? - Det litterära verket som vittnesmål och översättning
Bibliographic record
Abstract
Two brothers are riding the subway in Toronto. They have been spending some time in the city as guests of their family – aunts and cousins. Everyone is originally from Iran, but the brothers have lived most of their lives in Sweden. As the train rushes through the greater metropolitan area, the exasperation they feel, augmented by the sticky summer heat, starts consuming them, until they start speaking with each other. The one brother is annoyed by the way the other speaks Persian with their family. Little by little, the conversation evolves into an argument, and finally into a full-blown verbal conflict. Suddenly, they notice the other passengers are staring at them, and with a flash of shame they realize that the curiosity of the perplexed faces staring at them is because their animated argument has been conducted in Swedish – a language that sounds nothing like what would have been expected from two Middle Eastern men. The point of departure for this inquiry is the brothers’ ability and inability to express intimacy and conflict in a language that can only exist as translation. The inquiry attempts to answer the question of how this event can be written, when the context that constitutes the receiving end of the account is shaped by the colonial history of the West – that is, when the potential reader is informed by a colonialist and racist epistemology. The study explores the possibility of decolonial practices embedded in literary and poetic writing. What is found at the heart of the inquiry is the literary construction of the event, not the event itself. By putting language into play, not only as a system of signs used for communication or critical thought but also as a poet and writer’s concrete working material, the study explores what is characteristically literary in texts that are the result of artistic practices, and how such texts operate not only to report an event but to change their readers from spectators of the events to witnesses. In effect, this is an inquiry into the possibility of poetic and literary language to challenge and shift epistemic systems by way of non-symbolic language.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.043 | 0.016 |
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".