Bibliographic record
Abstract
Kinema Club is an informal community of scholars, artists, and fans interested in Japanese moving image media established in the early 1990s. A group that Initially formed for informally swapping Xeroxes of tables of content from Japanese film journals eventually established a newsgroup called KineJapan, which instantly grew to 50 names. KineJapan now has over 600 participants from every part of the world. \n \nFrom this description you might gather than Kinema Club is more an idea than a group. The idea is that Kinema Club provides a rubric within which anything is possible. No one owns it. Anyone can take it and do something creative with it. We have no dues (and no budget or bank account). No system of introductions. No office. It is amorphous, even anarchic, but it has definitely played an important role in networking all the scholars, programmers and fans interested in Japanese cinema. \n \nOne of the most important activities has been our workshops and conferences. At the end of the 1990s, the study of Japanese cinema was undergoing some interesting transformations. Most notably, it was becoming increasingly interdisciplinary. To confront these changes head-on, an intimate workshop was held at the University of Michigan in 1999. One thing became immediately evident: although there were many students and professors studying Japanese film and television, no one really knew each other. KineJapan already had over 200 members at that point, but few people had met face to face. So subsequent workshops and conferences were held in Hawai'i (2003), NYU (2004), McGill (2004), Tokyo (2005), NYU (2005), Yale (2006), Frankfurt (2007), Harvard (2009), Hawai'i (2010), Vienna (2011) and Yale (2012).
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.011 | 0.028 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.045 | 0.022 |
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".