The Failure of Form: Reading Liminality Computationally in Dostoevskii’s <i>The Double</i>
Bibliographic record
Abstract
Abstract This article uses computational text analysis to examine Fedor Dostoevskii’s The Double, responding to the long-standing critical debates surrounding the text and particularly its form, which Dostoevskii saw as having failed his idea. It asserts that the problem of the ontological status of Goliadkin’s double can be productively considered through an analysis of the text’s use of liminality, a hallmark of romantic fantastic literature. TEI-XML encoding of liminality identified in the text enables a series of visualizations that show that liminality is primarily concentrated in interior spaces. Analyzing the visualizations, the authors argue that liminality is associated with Goliadkin’s social shame, suggesting that the double is an extension of Goliadkin’s psychology rather than a fantastic apparition. Using The Double as a case study, the authors argue that computational text analysis can extend and enrich traditional philological methods by enabling deep structural analysis of the text.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".