Bibliographic record
Abstract
British Columbia is celebrated as Canada’s principal centre of audiovisual production. Its billion-dollar industry trails behind only California and New York, the most well-established film production sites on the continent. Prior to the mid-1970s, however, British Columbia had little in the way of film production that could properly be called an industry. This timely book recounts the story of British Columbia’s rapid rise from relative obscurity in the film world to its current status as “Hollywood North.” Mike Gasher positions the industry as a model for commercial film production in the twenty-first century – one strongly shaped by a perception of cinema as a medium, not of culture, but of regional industrial development. Addressing the specific economic and geographic factors that contribute to the province’s success, such as the low Canadian dollar and BC’s proximity to Los Angeles, Gasher also considers the broader implications of the increasingly widespread trend towards location service production on national cinema and cultural production. Hollywood North is an important book that brings into focus the tension between globalization and localization in the film industry. It will have great appeal to those with an interest in debates on Canadian national cinema, the notion of cinema as industry, and the highly nuanced relationship between cinema and place. Selected as a BC Book for Everybody.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.318 | 0.128 |
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".