Becoming Queer In/Human in Sasha Marianna Salzmann’s <i>Außer sich</i> (2017)
Bibliographic record
Abstract
This article examines the way in which Sasha Marianna Salzmann’s novel Außer sich (2017) blurs the boundaries between the human and the inhuman to challenge normative notions of humanity as clearly gendered. Focusing primarily on the protagonist’s transgender body, I analyze the textual instances in which inhuman entities (animals, parasites, objects) disrupt ambiguously gendered anatomies, materializing their dehumanized position under normativity. Drawing on the theorizations of queer inhumanism by Dana Luciano, Mel Y. Chen, and Eunjung Kim, I show how the novel turns the inhuman into an instrument of resistance against the coercive logics of the human through what I term “becoming queer in/human.” By letting the inhuman suspend the prerogatives of human morphologies, “becoming queer in/human” allows for alternative ontologies beyond the binary to become possible. In activating the productive potential of confusion, the narrative opens up the human and its genders to rearticulation, contributing to contemporary German debates in envisioning a different future for the transgender subject.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".