Bibliographic record
Abstract
Japan's first weekly, 30-minute animated TV series, Tetsuwan Atomu (Astro Boy), is not only commonly regarded as the first instance of what is now known as `anime'; it is also regarded as the point of emergence of the commercial phenomenon of character-based merchandizing. Interesting enough, it is not so much Tetsuwan Atomu the TV series as the practice of including Atomu stickers as premiums in the candy maker Meiji Seika's chocolate packages that really ignited the character merchandizing boom. The key to the success of the stickers — along with the use of the already popular figure of Atomu — was their ability to be stuck anywhere, and seen anytime. This anytime-anywhere potential of the stickers arguably led to the new communicational media environment and the cross-media connections that characterize the anime system and the force which drives it: the character. Part historical, part theoretical, this article will explore the thesis that it was the `medium' of stickers that led to the development of the character-based multimedia environment that is a key example of — and perhaps even a precursor to — the ubiquity of media that is the theme of this journal issue.
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 | 0.000 | 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 | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.066 | 0.016 |
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".