Bibliographic record
Abstract
Este artigo explora alguns poemas sobre o Brasil escritos pela canadense Jan Conn, poemas estes que são uma releitura da relação entre o Eu e o Outro nas Américas. Levando em conta o fato de que, por não possuírem tradições culturais ou histórias similares, o Brasil não é automaticamente considerado um Outro canadense (e vice-versa), procuro explorar a idéia (já discutida por críticos como Besner e Almeida) de que são justamente as diferenças entre os dois países que possibilitam descobertas surpreendentes. Uma destas descobertas acontece no choque entre práticas tradicionais de representação e a “realidade” do Outro na experiência da viagem. É nesse choque que o papel do sujeito (Eu) como construtor ou escritor do Outro começa a ser questionado e desestabilizado. Assim, neste trabalho, procuro demonstrar de que forma esta desestabilização acontece na obra de Jan Conn.Abstract: This paper approaches some of Jan Conn’s poems on Brazil as a re-reading of the relationship between Self and Other in the Americas. Aware of the fact that, because of their different historical and cultural traditions, Brazil is not automatically considered a Canadian Other (and vice-versa), I try to work with the idea (already discussed by critics such as Besner and Almeida) that it is exactly their differences that enable some surprising discoveries. One of these discoveries is linked to the shock between traditional representational practices and the actuality of the experience of the Other. Through this shock, the role of the Self as the constructor or writer of the Other is questioned and destabilized. This paper is an attempt to demonstrate how this destabilization takes place in Conn’s work.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".