Local Hollywood: Global Film Production and the Gold Coast
Bibliographic record
Abstract
Hollywood films and television programs are watched by a global audience. While many of these productions are still made in southern California, the last twenty years have seen new production centres emerge in the US, Canada and other locations worldwide. Global Hollywood has been made possible by this growing number of Local Hollywoods: locations equipped with the requisite facilities, resources and labour, as well as the political will and tax incentives, to attract and retain high-budget, Hollywood-standard projects. This new book gives an unprecedented insight into how the Gold Coast became the first outpost of Hollywood in Australia. When a combination of forces drove Hollywood studios and producers to work outside California, the Gold Coast's unique blend of government tax support, innovative entrepreneurs and diverse natural settings made it a perfect choice to host Hollywood productions. 'Local Hollywood' makes an essential contribution to the field of film and media studies, as well as giving film buffs a behind-the-scenes tour of the film industry.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".