A Corpus-based Lexical Study of Contemporary Feminist Short-Story Writers: with Special Reference to Alice Munro
Bibliographic record
Abstract
ملخص يعتبر هذا البحث دراسة نحوية مبنية علي علم المدونات لخصائص القصة القصيرة لللأدب النسوي مع الاشارة للکاتبة النسوية أليس مانرو. تهدف الدراسة إلي الکشف عن السمات اللغوية و تحديد المواضيع المتکررة التي غالبا ما تتناولها الکاتبة والتي تتعلق بالظروف المتدهورة للمرأة خلال القرن العشرين. يتم التحليل عن طريق القاء الضوء علي الالفاظ الأکثر شيوعا بالإضافة إلي البحث عن معانيها اللفظية و الدلالية و ملامحها المعجمية المختلفة و مدي دقتها في التعبير عن اتجاهات الکاتبة. بالإضافة الي ذلک, يلقي البحث الضوء علي أهمية إختيار الألفاظ في في تصوير الهوية الأنثوية التي تبناها أليس مونرو والتي تسود في معظم کتاباتها.ويعتمد البحث في الجانب التطبيقي على نظرية تحليل الألفاظ التي تبناها فيرث. Abstract This research is a corpus-based study of the lexical features in the short stories of the contemporary female Canadian feminist writer Alice Munro. The aim of the study is to specify recurrent themes related to the deteriorated conditions of women throughout the twentieth century through her lexical choices. The lexical analysis isanalyzedin terms of collocations, concordances, and lexical sets that are frequently used to convey such themes. In addition, the denotations and connotations of the most and the least frequent lexical items with various lexical features are analyzed. Throughout the analysis, special attention is devoted to how these lexical choices help portraying the feminine identity adopted by Alice Munro and prevailing in most of her writings. This is processed using AntConc 3.4.4 software.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".