Metodología para la clasificación de industrias culturales/creativas en una ciudad media: Culiacán, Sinaloa, México
Bibliographic record
Abstract
This analysis is aimed at schematizing a methodological proposal for classifying cultural/creative industries in Culiacan, and determining their contribution to production dynamics, based on the North American Industry Classification System, 2013, and the Classification Guide for the Canadian Framework for Culture Statistics, 2011. In view of the limited empirical construction on the subject in Mexico, the purpose is to carry out a classification useful for unifying the occupations involved in creation, production and distribution through domains in order to implement a regulation that specifies the operability of nine industries in this city, based on the statistical comparison by economic branches of the secondary and tertiary sectors. It follows that the volume and growth of detected activities, firms and employment delimit the cultural/creative industries which are apt for promoting the production system’s capacity in a local economic cluster. The classification is flexible and does not exclude omissions; it rather can be conceivable in other cities.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".