Reinvention and Appropriation of the Folk in Daler Mehndi’s POP Videos
Bibliographic record
Abstract
In the Indian context, where the folk and folk traditions are still prevalent, current cultural iconographies have the power to rework and reinvent existing forms. The folk, whether in Delhi, Jalandhar or Toronto, was reinventing itself in the form of a happy dancer. In contrast, the troupe of women dancers accompanying him in the videos are dressed in modern clothes – pantsuits, halters, shorts and minis. The Panjabi woman is represented here as streetsmart, an energetic dancer, and more often than not, unfaithful in love. The hypertext of Mehndi&s;s videos picturing the Sardar cavorting with assorted females repeated itself time and again, and with it, the viewers began to believe in its reality. The public imagination had already instituted the image of the Sardar as the soldier, one of the stock characters that are often appropriated as representations of a community.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| 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".