Motifs, textures and folds: Japanese popular visual culture as transcultural and phenomenological flow
Bibliographic record
Abstract
Since the 1980s, Japanese popular visual culture has known great popularity in Western Europe and North America, most strikingly in the form of manga, anime and Japanese video games. However, one is struck by how fragmented this cultural flow is: not only is it composed of three different media, but it also contains works that are wildly different from one another. Can something be said to connect these works together, other than their Japanese provenance? This dissertation proposes two avenues for answering this question and establishing a certain cohesiveness within the fabric of Japanese popular visual culture as it has been exported: on the one hand, this thesis explores recurrent content and themes (motifs) within a purposefully varied corpus of manga, anime and games; on the other, it establishes phenomenological consistencies (textures and folds) across the corpus, demonstrating that these works provide medium-based experiences that are similar in significant respects. Parallel to this demonstration, this dissertation examines the effects of this cohesion on the Western reception of these works. The author argues that, while cultural motifs evoking “Japaneseness” play an initial part in gathering these works into a perceived flow, it is their common phenomenology that cements their perceived cohesion and facilitates their integration into non-Japanese imaginaries. By analysing the transcultural travels of Japanese popular visual culture, this thesis examines a case where differentiated imaginaries meet and merge, and thereby develops a theory of the imaginary as phenomenological and processual space, as a fabric that surrounds us and which we collectively and continually weave and unravel. Ultimately, the author determines that this particular imaginary is regulated by two key notions: on the one hand, a dynamic of flux and stasis, and on the other, a series of interconnected and intermingled folds.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".