Bibliographic record
Abstract
Midnight at the Dragon Café, a novel by the esteemed Chinese-Canadian author Judy Fong Bates, portrays the experiences of three generations of Chinese immigrants in Canada through the perspective of Su-Jen. As members of a marginalized minority, they face both economic hardship and psychological struggles, further exacerbated by the constraints of a patriarchal society. These challenges foster a profound sense of alienation and estrangement, particularly for Su-Jen’s mother Lai-Jing, who not only endures systemic oppression from mainstream society but also experiences domestic pressures that contribute to her emotional detachment from others and herself. Erich Fromm’s theory of alienation, which explores human existential crises and psychological turmoil through the interplay of social structures, personal experiences, and psychological dynamics, provides a valuable framework for analyzing her estrangement. In light of the concepts of marginalization, loss of self authenticity and distorted relationships from this theory, this study seeks to uncover the underlying factors contributing to her disconnection from society, others and self. Through a hermeneutic textual analysis grounded in Fromm’s theory of alienation, this thesis aims to illuminate not only the roots and consequences of her emotional estrangement but also the broader struggles of women under patriarchal oppression and their ongoing pursuit of identity and self-authenticity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.015 | 0.009 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".