From Collective Amnesia to Shared Responsibility: Bridging Trauma in Haruki Murakami’s Kafka on the Shore
Bibliographic record
Abstract
In Kafka on the Shore (2002/tr.2005), Haruki Murakami explores the ambiguities surrounding Japan’s traumatic history and its lingering impact on contemporary generations. In the form of two parallel narratives, Kafka on the Shore juxtaposes the story of Kafka Tamura, a fifteen year-old runaway searching for his mother, with that of sixty year-old Satoru Nakata, a man who lost his memory in a strange episode during WWII. Initially isolated, both characters leave Tokyo for Shikoku (the smallest of Japan’s main islands), only arriving at their destination after accepting the support of others. Reaching across generational shores, friendships are used in the text to bridge the gap between past and present, personal trauma and collective amnesia. As affective gestures established outside traditional communities of belonging, these friendships teach characters new ways of interpreting their painful past, while allowing readers to reflect on their own sense of shared responsibility.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.016 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| 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".