Bibliographic record
Abstract
Film and television production are important components of the Canadian economy. In Vancouver, popular American television series like The X-Files and Canadian series like Da Vinci's Inquest have boosted the city's profile as a centre for international and domestic productions. Serra Tinic's On Location is the first empirical analysis of regional Canadian television producers in the context of developing global media markets. Tinic observes that global television production in Vancouver has been a contradictory process that has, on one level, led to the homogenization of culturally specific storylines, while simultaneously facilitating the development of new avenues for international ventures. The author explains how federal and regional network considerations, funding guidelines, and partnerships with international co-producers affect the capacity of Canadian television producers to negotiate culturally specific storylines in the development process. She further interrogates the concepts of globalization, culture, and national identity, and their relationship to broadcasting from the perspectives of members of the television industry themselves, highlighting the extent to which industry practices in Vancouver epitomize current trends in global television production. On Location fills a major gap in contemporary media and cultural studies debates that question the connections between the politics of place, culture, and commerce within the larger context of cultural globalization.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".