Technique of Exploring Women’s Choice in Select Novels of El Sadaawi, Ba, Alkali and Adichie
Bibliographic record
Abstract
Women writers in Africa have enjoyed wider audience especially in higher institutions where the curriculum includes African Women Writers, Gender Studies and other related courses. African women writers may focus on a variety of subject matters but what is common to their literary art is that they concentrate on the experience of women. This article focuses on how the authors use their literary art to portray women’s experiences in their social melieu. Nawal El Sadaawi, Mariama Ba, Zaynab Alkali and Chimamanda Ngozi Adichie are women writers from Africa. The first three women are older and from Moslem background. Adichie is younger and from a Christian background. The choice made of the novels of these women is due to the recurrent problem of being a woman everywhere. In contemporary times women are still treated differently just because they are women. However, it has been observed that there is nothing intrinsic in women that depict them as the bad or inferior species of human beings. This article focuses on the commonality of style used by the select African novelists in couching the predicament of women in the African society. The novels chosen in this research are El Sadaawi’s Woman at Point Zero and God Dies by the Nile; Ba’s So Long a Letter and Scarlet Song; Alkali’s The Stillborn and The Virtuous Woman and Adichie’s Americanah.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".