Gender Disparity in School Textbooks in Jordan: The Case of Arabic and Social Education in Grades 4, 5, and 6
Bibliographic record
Abstract
Representation of females and males in language and school textbooks is a determinant factor in the perpetuation of gender socialization of children and the normalisation of their gender roles and positions. School textbooks often portray boys and girls adhering to gender stereotypes, with girls associated with housework and childcare, and boys associated with labor and leadership. This paper reports the gender disparity with reference to sexist language, content, images, and illustrations in current Jordanian school textbooks pertaining to the two subjects in contemporary Jordanian textbooks: Arabic Language and Social/Civic Education. Twelve textbooks of both subjects for Grades 4 - 6 are selected for content analysis. The research concludes that women and girls were either marginalized or symbolically annihilated in the content and language of the selected school textbooks. Content analysis of textbooks is crucial to influence gender-sensitive reform of school curricula through careful analysis of the linguistic, visual and thematic content. To this end, the paper draws attention to the existing sexist language and sexist content in school textbooks to identify areas for curricular reform advocating for gender equality.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".