“Warm blood and live semen and rich marrow and wholesome flesh!”: A Queer Ecological Reading of Christopher Isherwood’s A Single Man
Bibliographic record
Abstract
In Christopher Isherwood’s A Single Man, George, the novel’s main character, acts a barometer for the ecological destruction enacted by the “breeders”—the families and their children—who surround him. While mourning the sudden death of his longtime partner, George observes the suburban heterosexual couples and their offspring as well as the rampant growth and construction and the general environmental destruction occurring in California at the time. While the novel is traditionally read as a text that empowers and normalizes a gay man in a long-term relationship, I argue that these critics are ignoring the environmental signs spread throughout the novel. George notices the urban and suburban sprawl occurring in California, and he realizes that the sprawl (and humans) will die and “the desert, which is the natural condition of this country, will return” (A Single Man 111). Isherwood specifically uses his gay character to track the inevitable apocalypse that will be brought on by breeding and reverses the paradigm of queerness as unnatural by making reproduction unnatural and inherently apocalyptic. Besides this, George constructs spaces to support his queerness as well as the preservation of natural spaces. And instead of imposing new binaries in the narrative, Isherwood includes descriptions of touch and play, primarily that between George and his student Kenny, as a means of dissolving boundaries and opening upon the possibility of naturalized same-sex eroticism.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.017 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".