Bibliographic record
Abstract
This work provides an insightful analysis of Mary Shelley’s exploration of social norms, otherness, and acceptance in Frankenstein. It examines how Shelley challenges traditional perceptions of beauty and humanity through Victor Frankenstein's endeavour to create life, leading to moral dilemmas. The paper highlights how the creature's marginalised existence reflects social biases, driving him to retaliation. Victor's failure to acknowledge the humanity of his creation underscores themes of accountability and compassion. The paper emphasises Shelley's juxtaposition of Victor's actions and the creature's plight to expose society's inclination to ostracise deviations from the norm. Furthermore, it thoroughly examines creator-creation intricacies and the "self" versus the "other" theme, critiquing society's tendency to vilify the "other" as a monstrous entity devoid of identity and human essence and characteristics. The analysis stresses the need for understanding identity deprivation and the construction of monstrosity in society. This comprehensive examination sheds light on the intricate interplay between social norms and individual identity, urging a reevaluation of social treatment towards those perceived as different or 'other.' Through Shelley's narrative lens, the paper navigates through the complexities of moral responsibility, compassion, and social prejudices, inviting readers to reflect on the broader implications of human relationships and social constructs depicted in Frankenstein.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.048 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".