Realizations of Conversational Implicatures in The Great Gatsby-A Psycholinguistic Perspective
Bibliographic record
Abstract
The studies of conversational implicature mainly focus on discourse analysis, but relatively few studies are from psychological perspective. This paper aims to investigate how specific words and silence of the masterpiece The Great Gatsby manifest conversational implicatures related to psychological states. The paper is based on the corpus of chapter seven from The Great Gatsby, with high frequency words (i.e. ‘the’, ‘and’, ‘well’, ‘heat’) selected quantitatively in statistics using corpus linguistics methods such as segmentation, clustering, and frequency. The analysis of examples extracted from the novel could manifest that specific words as well as silence are psychologically adequate for conversational implicatures. The psychological accounts of conversational implicature are convincing in the novel, not only rendering it a masterpiece but also leading us to the inquiry of psychologically-based implicatures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".