The Study of Literary Criticism on The Well of Loneliness from the Perspective of Toulmin’s Argumentation Model
Bibliographic record
Abstract
Literary criticism is a kind of commentary genre, with a certain color of argumentation. Toulmin’s model, as an important method of non-formal logic, has played an important role in the analysis of argumentative discourse (Yang, 2004). Therefore, it also provides a new perspective for the study of literary criticism. This paper, on the basis of consummating Toulmin’s model, analyzes different specific arguments of The Well of Loneliness, this controversial literary work whether can become a literary classic and widely recognized in different times, combined with literary criticism, and tries to characterize the internal structure of the argumentation, analysis of the dynamic process of argumentation and improvement of the pragmatic strategies of argumentation in a finer way. Thereby, it is more rational to verdict and to verify the rationality and effectiveness of the argumentation. Then suggestions of the construction and perfection of literary criticism can be provided.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.024 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 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".