Representation of Males and Females in Myanmar Culture through a Selection of Myanmar Literary Works in English
Bibliographic record
Abstract
<p class="1Body">In Myanmar, although men and women have equal rights under the customary law, conservative cultural belief prevents to enjoy these rights between men and women. Therefore men are still superior and women are subordinate in Myanmar society. To reach a better understanding of whether equality exists between men and women in Myanmar society, a particular type of literary work which is reflection of Myanmar culture can be explored. Therefore, Myanmar short stories, written originally in English by Myanmar author Daw Khin Myo Chit and the selection of Myanmar short stories written originally in Myanmar by various kinds of Myanmar authors but translated into English by Myanmar writer Ma Thanegi, are chosen to be investigated. The aim of the present study is to investigate the way in which males and females are represented in Myanmar short stories which reflect Myanmar culture. Gender analysis by Khurshid, Gillani, and Hashmi (2010) is conducted to analyze the data. The quantitative and qualitative methods were used to analyze short stories. It is found that the data found in Daw Khin Myo Chit’s short stories and Ma Thanegi’s translated works were the same. The results showed that there is no significant difference between males and females except occupational roles. It can also be observed that in analyzing Myanmar short stories, although women play the important roles as equal as men in most cases, women are still inferior rather than men according to Myanmar culture and Myanmar tradition.</p>
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".