A Semiotic Analysis of Gender Discursive Patterns in Pakistani Television Commercials
Bibliographic record
Abstract
The study is multidisciplinary that ventures into the domains of semiotics, linguistics and cultural studies. Media has become one of the most viable social institutions of disseminating information to a wider audience. It has got power to (re)frame the ideology of larger audience through its visual/linguistic content and to pave the way to social change. The current study aims to investigate the manifestation of gender discursive patterns in the Pakistani television commercials. This study draws its theoretical foundation on the theory of semiotics propounded by Dyer (1982) in her book Advertising as Communication. Semiotics is conceived an appropriate tool for the critical inquiry of the televised commercials because of its wide ranging acceptability and reliability in the meaning making process. Williamson (1978), Dyer (1982) and Jhally (1990) not only recommended but they also practically employed semiotics as a tool of investigation for critically examining the meaning making process in the commercials that enhances the reliability and validity of semiotics as a tool of inquiry. The data for the current study comprises television commercials broadcasted on famous Pakistani television channels. The sampling technique is based on non-probability purposive sampling. The rationale of choosing purposive sampling technique is to include only those commercials which reflect gender representation. The findings of the study highlight that the commercials present layers of meanings via semiotic modes at symbolic level where men and women are displayed in stereotypical manner. The existing gender narratives in the Pakistani commercials subscribes to patriarchal structures. The study presents recommendations about the change in the content of the televised material and also highlights the unexplored avenues which can be brought under considerations by the future researchers.
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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 | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".