Critical Discourse Analysis of the Symbolic Language in Shakespeare’s Selected Dark Lady Sonnets
Bibliographic record
Abstract
The English national poet William Shakespeare wrote 154 sonnets, which are commonly divided into three categories: the “Fair Youth Sonnets” (126 sonnets), the “Dark Lady Sonnets” (26 sonnets), and the “Greek Sonnet.”(02 sonnets). The current study aims to conduct a critical discourse analysis of the symbolic language employed in Shakespeare’s Dark Lady Sonnets. A content analysis method was adopted to examine the data. The study's population includes the 26 sonnets, known as “Dark Lady Sonnets”. Using a purposive sampling technique, the researchers selected six sonnets (127, 128, 129, 130, 131 and 132) from the Dark Lady collection as the sample for data analysis. The findings reveal that Shakespeare effectively utilized symbolic discourse throughout these selected sonnets. This study offers valuable insights and is expected to serve as a useful resource for future researchers and literary scholars.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".