The Realization of Figure and Background in Li Qingzhao’s Poems
Bibliographic record
Abstract
Abstract The rapidly rising cognitive poetics at the late 20th century is the novel interdisciplinary scientific tool between cognitive linguistics and literary criticism to interpret literary works. Figure and background separation principle is one of its main researches. Initially using this principle to study literary works, Stockwell and Tsur focus on the readers’ psychological cognitive mechanisms involved in comprehending literary discourse and conclude that figure and ground segregation principle are the fundamental characteristics of literary stylistic analysis. This paper mainly discusses its realization in Li Qingzhao’s poems and Ci-poems and its effects on formation of artistic conception, in hope of providing a new model for studying Chinese classical poems. Resume La montee rapide poetique cognitive a la fin du XXe siecle est le nouvel outil scientifique interdisciplinaire entre la linguistique cognitive et critique litteraire pour interpreter des œuvres litteraires. Principe de separation de la figure et le fond est l’une de ses principales recherches. Initialement a l’aide de ce principe pour etudier des œuvres litteraires, Stockwell et Tsur mettre l’accent sur les mecanismes cognitifs psychologiques du lecteur impliquant a comprendre le discours litteraire et concluent que le principe de segregation de la figure et le sol est les caracteristiques fondamentales de l’analyse stylistique litteraire. Cet article traite principalement de sa realisation dans les poemes de Li Qingzhao et Ci-poemes et ses effets sur la formation de la conception artistique, dans l’espoir d’offrir un nouveau modele pour l’etude des poemes classiques chinois
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".