“Mother” in Aytül Akal’s Stories within the Context of Social Gender Perception
Bibliographic record
Abstract
Just as many factors are of question in one’s identity, so is the way to present the characters in literary books. Presentation of characters on equality basis is very important so that democratic culture and human rights related values are acquired. In this study, mother image fictionalized by Aytul Akal in her stories of children is dealt with in terms of social gender. The study was conducted through document analysis design. We have reached and examined all of the story books written by Aytul Akal for children. Nine of these books were written by Aytul Akal herself while only two in cooperation with Mavisel Yener. The data were collected based on studies on social gender and researches on quality of children’s books during literature review then the data collected were classified for archival reasons while they were classified for purpose of record. Secondly, story books written by Aytul Akal for children were examined and the image of father and mother were encoded and recorded by two researchers and one qualitative research specialist. The data analyzed descriptively were exposed to content analysis for detailed information. As a result, it was found that the character attributes on image of mother in Aytul Akal’s works were closely related with her roles in home and work life. Since mother was as someone dealing with home work, children and work, from time to time she experienced difficulties. This shows that traditional image or understanding of mother in the stories did not essentially change and the workload of mother was stable while her work outside home increased. The present study aims to assess the mother image in Aytul Akal’s stories based on the social gender perspective.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".