The big pictures: sources of national competitiveness in the global movie industry
Bibliographic record
Abstract
The competitive dynamics of the global film industry are not frozen in time. The Motion Picture Association of America (MPAA) studios have pursued an utterly transparent strategy of buying out or otherwise dominating their domestic and international distribution chains, while generally avoiding cooperation with other nations’ producers. This strategy has gone unchallenged largely because other nations and film production companies have lacked perspective on their own position and potential in the global film industry. With keener use of existing tools, including co-production, these countries can establish themselves. For instance, Canada, having co-production treaties with both mainland China and Hong Kong while no other nation has co-production treaties with either, has uniquely positioned its film industry to enter the Chinese mass market either directly or via Hong Kong’s free trade without the crippling import expenses that other foreign producers face. However, Canada’s producers to date have made less creative use of the co-production treaty with China, using it to more easily access low-cost animation inputs.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.001 |
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".