Indonesian Stand-Up Comedy: A New Developing Industry of Youth Culture
Bibliographic record
Abstract
The research analyzed the growth of stand-up comedy in Indonesia, which had developed into a new trend or popular culture and a new creative business that produced skilled and well-known comics. Furthermore, it discussed how stand-up comedy might develop into a new creative business by evaluating the growth of the community, Instagram, and YouTube, as well as the growth of successful comics. In order to help the researchers doing the analysis, the researchers applied a qualitative method. They used two theories named Self-presentation concept by Goffman and Creative Industry theory by Richard Florida. The findings indicate that the creative industry does not always progress forward; interest in stand-up comedy decreased in various places, but it is still attempting to develop. Indonesian people are becoming more receptive to stand-up comedy as it is home to some of the world's most talented comics. Comics must be innovative in their approach to content creation to increase their popularity and viability. Apart from that, when comics are popular, they can inspire others to pursue careers as comics. As a result, comics members continue to grow in number, the community grows in size, and the creative business continues to flourish. Stand-up comedy has developed into popular culture and a new creative sector geared toward youth.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".