The Truth Behind Voice and Power in My Feudal Lord: A Speech Act Analysis
Bibliographic record
Abstract
Female writers use autobiography to express their experiences, deference, and inner-conflicts. They describe their connection to different events and people in domestic or social context to explain their feelings and complexity of their lives. This study analyzes the way Durrani constructs norms of gender and power in her autobiography, My Feudal Lord. The paper imports Searle’s theory of speech act analysis to discover the way the author creates and performs gender in the domain of power through textual interactions. Durrani achieves the effect of patriarchy through frequent use of directives, expressives, and commissives by her husband through employing direct language. The husband openly expresses criticism, blame, complain, and acknowledgement in his interactions which validate his authority over his wife. The striking feature of the wife’s speech is even more frequent use of directives as compared to the husband. However, the major gender distinction was reflected in the use of directives. The husband used more commands and the wife asked more questions. Another major difference was that of commissives which occurred half of the times in the wife’s speech as compared to her husband’s speech. She hardly used any apologies or compliments which shows her diminishing submission to her husband’s authority. Her expressives also reflect her firm attitude and courage to take risk of protesting against her physically and socially more powerful husband.
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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 | 0.000 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".