Sino-Canadian documentary coproduction: transnational production mode, narrative pattern and theatrical release in China
Bibliographic record
Abstract
This article examines a series of coproduction practices undertaken by Canadian and Chinese documentarians against the backdrop of international interest in China, increasing transnational exchange and China's booming film market. First, it compares two documentaries about similar subjects, the Canadian-made Up the Yangtze (2007) and the Chinese-independent-made Bing Ai (2007a). The divergent approaches taken by these two films result partly from their different modes of production and target audiences (or lack thereof). It then investigates the production of Last Train Home (2009), for which Chinese and Canadian filmmakers collaboratively assembled economic and creative recourses and transformed a Chinese story to meet the needs of an international market. Modelled on Up the Yangtze, Last Train Home articulates the life fragments of a migrant worker family as a similar ‘figures in history’ narrative and underscores global interconnectedness and dramatic storytelling to engage global viewers. Finally, it analyses China Heavyweight (2012), an officially approved coproduction, which sought to access the untapped mainland Chinese film market. These practices demonstrate the potential of coproduction as ‘production technology’ (Baltruschat 2010. Global Media Ecologies: Networked Production in Film and Television. Abingdon: Routledge). I emphasise their significance in establishing a new model for Chinese documentarians in multiple dimensions including transnational production mode, narrative pattern and theatrical release.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".