Defiance in the Shadows: Flames of Resilience in the Selected North Korean Memoirs
Bibliographic record
Abstract
The resilient autobiography focuses on the interpersonal dynamics of life narratives, including the relationships that have exacerbated the hardships described and the ones that have provided the support and strength necessary to overcome them. The selected text for this paper is A Thousand Miles to Freedom: My Escape from North Korea by Eunsun Kim and Sebastien Falletti and In Order to Live: A North Korean Girl’s Journey to Freedom by Yeonmi Park and Maryanne Vollers. These two texts talk about their catastrophic journey from North Korea because of poverty caused by famine and their migration to China, where they were trafficked and subjected to humiliation and their final escape to South Korea. The memoirs depict the individual’s embodiment of resilience as they narrate their own struggles and victories in overcoming hardship. Resistance to adversity and suffering, as well as the ability to bounce back from painful experiences in one’s own life and in the lives of others, are the hallmarks of resilience. Trauma becomes ingrained in attempts for survival in both memoirs, which illustrate the catastrophic impacts of famine, relocation, and personal loss. One effective approach to enhance resilience is reorganizing and reestablishing control over one's life after a traumatic event. Interpretations and writings of the personal narrative are offered from both the subject’s and an outsider’s points of view. Thus, the life story is formed in a dual sense: autobiographically and biographically.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.011 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".