“[A] mad excess of love”: Hyper-Sympathy, Fidelity, and Suicidality in Mary Shelley’s <i>Falkner</i> <sup/>
Bibliographic record
Abstract
Mary Shelley’s Falkner depicts a sentimental and self-destructive hero whose extreme feeling leads, however unintentionally, to the death of his beloved. According to Shelley, left unregulated, emotions—and sympathy in particular—have the potential to not only encourage immoral behaviour but to provoke suicidal ideation. Yet, paradoxically, when felt to excess, sympathy can also prevent an individual from acting on her suicidal thoughts and infringe on her basic human liberty, her right to die. Although Falkner longs for death, believing that by destroying himself he will atone for his crime, he is prevented from doing so by the fervent sympathy of his adopted daughter Elizabeth, who will not permit him to take his own life. As this article argues, hyper-sympathy in Falkner is presented in a surprisingly sinister light, for it precipitates criminality, gives rise to suicidal ideation, strips an individual of his autonomy, and prolongs rather than relieves suffering.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.017 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| 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 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".