Violence Against Women in Sanaa Shalan’s Falling in the Sun
Bibliographic record
Abstract
Violence against women is a heinous act committed against a woman, a wife, a mother, a sister, or even a daughter deliberately or not deliberately causing her psychological, emotional, and physical harm. The rise of this unhealthy phenomenon mainly in less-developed countries such as Jordan necessitates more academic attention not only because of its detrimental effect on the Jordanian women’s lives, but also because it is intentionally ignored and dismissed as taboo. With that, there has been a growing interest among Jordanian writers and sociologists in exploring the extent of this social ill through creative literary genres such as novels. This paper for one primarily examines the manifestations of violence against women in the Jordanian context through a textual analysis of Falling in the Sun by Sanaa Shalan, an author hailing from the contemporary Jordanian generation. Originally written in Arabic, this well-known novel gives prominence to the severe reality of the distress habitually suffered by many Jordanian women, notably the various forms of violence that they have to tolerate living in a multicultural male-controlled nation. With a feminist reading of Falling in the Sun (2014), we shall examine Shalan’s representations of violence against women in the novel as a dire social illness resulting from mistaken social beliefs, absence of laws, and misunderstanding of religion and gender inequality in the Jordanian society. Additionally, the current paper’s outline is constructed on three main forms of violence against women, i.e. physical, psychological and economic abuse as depicted in Falling in the Sun through the novel’s female characters, primarily the main protagonists.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.011 | 0.007 |
| 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".