Bibliographic record
Abstract
This article aims to analyze how the nameless female narrator overcomes victimhood complex, refuses to be a victim, and becomes a creative non-victim based on the concept of “becoming-animal” developed by Gilles Deleuze and Felix Guattari in Margaret Atwood`s Surfacing. The narrator, who visits Quebec in search for missing father, feels uncanny when she faces the villagers speaking French on her home ground, foreign territory. According to Freud, the uncanny is in reality something familiar and old-established in mind but becomes alien from it only through the process of repression. The narrator recalls her memories related to death and violence as a hidden force. She only admits herself as a victim and victimizer, who aborts her baby, but also tries to explain this as the dictates of biology, namely, due to her false husband`s coercion. Also, she experiences violence and evil done by Americans such as killing a heron like a lynch victim and trying to occupy the islands. After perceiving her past fault and the origin of the great evil, she refuses the assumption that she is a victim. Finally, she performs to become a creative non-victim, which means beyond overcoming victimhood. The narrator`s free movement and metamorphosis through becoming animals, plants, things and places can allow herself to recognize her anguish as a victim, revise her memories correctly, and conjoin different genealogies in the wilderness in Canada The narrator transforming into all the different things means that she immerses herself in the flow of the perception of life, which expands to its highest power by becoming hybrid. She expands to what is more than herself through transforming to be hybrid, open to “the event of becoming”.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".