A Sociopragmatic Analysis of Women and Gender Roles in John Galsworthy’s Forsyte Saga and Naguib Mahfouz’s Cairo Trilogy
Bibliographic record
Abstract
This study is concerned with investigating the treatment of women and gender roles in Glasworthy’s Forsyte Saga and Naguib Mahfouz’s Cairo Trilogy from a sociopragmatic perspective. The texts studied for this paper have not been evaluated to socio-pragmatic analysis that reflects the little application of this approach to literary works. As thus, the goal of this paper is to advance sociopragmatic analysis to these novels—there is salience from the style, narrative techniques, and language utilized by both writers in their books, which indeed points to pragmatic undercurrents that must be explored. The results indicate that social and political aspects are key elements for understanding women and gender issues in the selected texts. The integration of these contextual elements revealed how the two authors manipulated literary discourse to reflect on the power relations and struggles between men and women of their age. It can be claimed that sociopragmatic approaches provide opportunities for understanding the hidden layers within the selected texts in terms of social practices and interactions among characters. It is finally suggested that sociopragmatic approaches should be integrated into literary studies for a better and deeper understanding of literary discourse in general and crosscultural issues in particular.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".