Film and Television Sector Profile(1)- Argentina
Bibliographic record
Abstract
While Argentina's cinema audience declined during the first years of the country's four-year recession, Argentinians--who are enthusiastic consumers of cultural industries--returned to the movie theatres beginning in 2000. Movies comprise the only cultural sub-sector that didn't suffer due to the 2001/2 economic crisis and by 2003, the number of film goers rose to 32.6 million. However, significant differences between the behaviour of audiences in the City of Buenos Aires and in the rest of the country can be registered. In 1995, 70 % of the national audience lived in Buenos Aires, while in 2003, the majority or about two thirds lived in cities other than Buenos Aires. The explosion in audience numbers outside of Buenos Aires can be explained in part by the novelty of new shopping malls appearing in almost every city, featuring major movie theatres that have been built and managed by international chains. Nevertheless, citizens of Buenos Aires went to the movies 3.4 times on average during 2003, more often than other Argentinians, who on average went only once. Among film goers in Buenos Aires, 39 % attended movie theatres at shopping malls. During the first six months of 2004, nearly 22.8 million movie tickets were sold in Page 1 of 18InfoExport- The Canadian Trade Commissioner Service
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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 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.200 | 0.057 |
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".