Bibliographic record
Abstract
Cartoons, these days have become an integral part of every child’s childhood. They are amongst the most prominent forms of entertainment for children. With the advent of the nuclear family and single child families, with no mate/partner to interact, play or learn from, it is with the help of cartoons that kids are exposed to the various facets of the world around us. Cartoon films screened on most TV sets in Indian homes were majorly dubbed versions of successful cartoon films from USA, Japan, Canada, etc. From around 2003 onwards, some Indian cartoons started to appear on TV especially after the Cable TV came to Indian homes. This paper looks at the cartoons, which are made in India, made for India, and their co-relations with the cartoons which are otherwise screened on Indian TV sets, which are dubbed versions of cartoon films from around the world. These Indian cartoons are analysed and correlated with each other based on various attributes namely, the locale, the age of the protagonist, number of episodes, number of character in the movie, gender ratio, etc. The observations and conclusions done in this study are enlisted and presented. Keywords: cartoon films, children’s television, comparative analysis, gender stereotypes, social science research
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".