Bibliographic record
Abstract
This study tells the life stories of four Saudi female artists. Using life story narrative approach, I focused on the following research questions: How are Saudi female artists fulfilling their aspirations as artists in the conservative Saudi society? What are the common and divergent themes in the life stories of the Saudi women artists, namely Safeya Binzagr, Maha Almalluh, Tagreed Albagshi, and Fida Alhussan? The artists were interviewed using open-ended questions and asked to discuss their artwork. The postmodern feminism and social construction theories were used to understand their life experiences and how they came to be “successful artists” in the conservative Saudi society. The findings showed that family and formal education played an important role in these women’s life journeys as artists. The Saudi society was also a major influence, sometimes supporting them, at other times obstructing them. These artists share many personality features such as being persistent, believing in themselves, taking risks, facing challenges, being independent, being responsible as artists and as part of society, and being honest in their artwork. This study contributes to the art education curriculum in Saudi schools and universities. Globally, it contributes to women’s studies and to social and cultural studies in shedding light on the Saudi society, especially as it is experienced by women.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".