‘Becoming a Raven’: Self-Representation, Narration, and Metaphor in Fukase Masahisa's ‘Karasu’ Photographs
Bibliographic record
Abstract
One of the most poetic and mysterious photographic projects of the post-1945 period, Fukase Masahisa's ‘Karasu’ [Ravens] is here examined in relation to the photographer's entire body of work, his writings, interviews with his family and friends, and consideration of the influence of loss, melancholia, and psychological instability in his art. Although Fukase remains associated with the ‘personal photography’ movement of the 1960s and 1970s, it is argued that he was, above all, a committed experimenter in photographic narration and self-representation, factors important to the reading and understanding of ‘Karasu’. Claims that the ravens in Fukase's images symbolically represent a life now regarded as tragically sorrowful and ill-fated are evaluated and partly challenged.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.017 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".