Investigating Kurdish Women’s Experiences With Education in Kurdistan With Respect to Oppression
Bibliographic record
Abstract
The following thesis provides a qualitative study that sought to answer the question: What do Kurdish women’s experiences reveal about women’s education in Kurdistan with respect to oppression? The study was framed within a postcolonial feminist framework to investigate Kurdish women’s lived experiences within education in the Kurdistan Region of Iraq (KRI). The study used feminist research methods to collect and analyze data. Through purposeful sampling, 5 Kurdish women living in the KRI were recruited and interviewed by the researcher through one-on-one, semi-structured interviews. The researcher used an interpretive approach for data analysis to investigate participants’ experiences as women and as members of an ethnic minority. The study was conducted through a postcolonial feminist lens, which highlighted the unique social categories in which Kurdish women find themselves. The study found that the women’s lived experiences were determined by the intersections of gender, ethnicity, religion, location, SES, and age, among other social categories. Such categories affect women’s quality of life, freedom, and education, as identified by the women themselves. Further, the women identified the following factors acting as barriers that impede their equal access to education and opportunities: gender norms, family, culture, distance, disability, language, and conflict. The study also lays out how women make sense of and cope with such barriers and inequality, before concluding with recommendations for changes based on participants’ knowledge and lived experiences.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".