Bibliographic record
Abstract
This study undertakes a comprehensive examination of neurofiction – a genre of literary fiction which has emerged in response to what scholars have termed neuroculture. Neuroculture refers to the cultural ascendancy of neuroscience witnessed by Anglo- American society over approximately the past thirty years, and the associated predominance of materialist conceptions of consciousness. By examining works from four authors – Oblivion (2004), by David Foster Wallace; The Echo Maker (2006), by Richard Powers; Enduring Love (1997) and Saturday (2005), by Ian McEwan; and The Sorrows of an American (2008), by Siri Hustvedt – this work of contemporary cognitive historicism establishes and explores three grounding themes of neurofiction: pessimistic biologism, neuro-introspection, and neuro-intersubjectivity. Pessimistic biologism refers to a demoralizing view of human existence as dispiritingly mechanistic and existentially isolated; neuro-introspection refers to the the capacity for individual minds/brains to perceive and observe themselves; and neuro-intersubjectivity refers to the capacity for individual minds/brains to engage in forms of communication or empathy with their analogs. This study demonstrates how these three overarching themes frame and motivate the neurofictional works of my four authors, and how my conception of neurofiction brings into sharper focus other concerns of the genre. These other concerns include the so-called Hard Problem (the disconnect between, and irreconcilability of, objective and subjective accounts of consciousness); the Two Cultures (a perceived epistemological and philosophical clash between scientific and humanistic forms of enquiry); forms of obscured mysticism or spirituality; and the question of the value of fiction in the neurocultural era.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.034 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".