Bibliographic record
Abstract
16th SHANGHAI INTERNATIONAL FILM FESTIVALShanghai is playing an interesting hand early into its tenure as China’s most established festival, shaped by the Chinese film industry’s dynamic growth and the Beijing International Film Festival’s upstart claim for national preeminence. It could play its ace in promoting Mainland Chinese films, yet Shanghai hasn’t exploited this potential. This leaves Asian programming as its next best card, but Asian films at its 16th edition (15–23 June 2013) lacked range and vigour, especially in its fevered Japanese and Thai line-ups. Retrospectives felt more visible this year: apart from ones dedicated to Alfred Hitchcock, Ozu Yasujiro, Oliver Stone and Tang Xiaodan, Shanghai paid a nine-film tribute to the late singer-actor Leslie Cheung on his tenth anniversary. But organizers denied the same courtesy to Anita Mui, an equally talented hyphenate who also died in 2003, and whose amity and working rapport with Cheung certainly...
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 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 | 0.004 |
| 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) | 0.000 | 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".