Research Article The Nanking Atrocity: Still and Moving Images 1937–1944
Bibliographic record
Abstract
Abstract: This manuscript investigates the facts of publication of the images of the Nanking Atrocity (December 1937–January 1938) in LIFE and LOOK magazines, two widely read United States publications, as well as the Nanking atrocity film clips that circulated to millions more in American and Canadian newsreels some years later. The publishers of these images were continuing the art of manipulation of public opinion through multimodal visual media, aiming them especially at the less educated mass public. The text attempts to describe these brutal images in their historical context. Viewing and understanding the underlying racial context and emotive impact of these images may be useful adjuncts to future students of World War II. If it is difficult to assert how much these severe images changed public opinion, one can appreciate how the emerging visual culture was transforming the way that modern societies communicate with and direct their citizens ' thoughts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 teacher head, 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".