Towards Archival Justice: The Case of Nogŭn-ri Massacre During the Korean War
Bibliographic record
Abstract
This paper discusses the social production of archives with a focus on the archive of the Nogŭn-ri Massacre, a case of mass violence against South Korean civilians by US forces during the Korean War. Recent scholarship has criticized views of archives as stable repositories for documents, and instead has shown the process through which archives are constructed through divergent social forces. Moreover, scholars have encouraged archivists to actively function as conduits for the voices of marginalized counterpublics. The archive of the Nogŭn-ri Massacre itself is shown to have been formed by survivors and activists who demanded an apology and redress from the US military for the massacre. This counterpublic archive was first formed of oral testimony, but increasingly accumulated a growing number of written US military documents repurposed by the activists in the service of archival justice.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.047 | 0.019 |
| Scholarly communication | 0.018 | 0.013 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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".