"Hello, abattoir!": Becoming Through Slaughter in Miriam Toews’s A Complicated Kindness
Bibliographic record
Abstract
Drawing on the tradition of both the Bildungsroman and the Kunstlerroman , Miriam Toews’s A Complicated Kindness (2004) presents animal slaughter as the central symbol of adolescent becoming. In her depiction of Happy Family Farms, the local chicken processing plant in East Village, Manitoba, Toews offers a rigorous critique of the ways in which the town resists its own cultural erasure by rebranding itself as a town open for business – in this case, factory farming. Because a career at the abattoir is one of the few vocational opportunities open to young people like conflicted Mennonite teenager Nomi Nickels, Toews builds narrative suspense by alluding to the job awaiting Nomi if she chooses to remain in East Village. True to the dynamic structure of the novel, Nomi defers this decision, thus rejecting the closure of having become for the more episodic process of becoming . In this way, Toews crafts an ironic commentary on the teleology of coming-of-age narratives.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.031 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| 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".