DONG-MEI'S PROCESS IN ACCEPTING HER CHINESE IDENTITY TING-XING YE'S THROWAWAY DAUGHTER
Bibliographic record
Abstract
Throwaway Daughter is a story which tells about the searching of ethnic minority identity. As what the title implies, the story is about a girl who was abandoned and neglected by her parents in China. Dong-mei Margaret Parker is the throwaway girl who was then adopted by a Canadian family. Along with her physical development, she realizes that she was different from her White family. Ironically, she rejects her Chinese identity which is attributed to her. Dong-mei thinks that she is an unwanted daughter of her biological Chinese parents who had thrown her away to the orphanage because they disliked her. However, her opinion turns to be a curiosity after she learns much about China and its culture. She is eager to know more about her origin and especially about her biological parents. Her process from rejecting until successfully dealing with her Chinese identity and biological parents is the interesting topic to be analyzed. Nevertheless, the effort in gaining decent interpretation may not be realized unless it is supported by appropriate approaches and theories.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.017 | 0.010 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| 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".