Illuminating Feminine Pulchritude in Contemporary Advertisements of Cosmetic Products: A Semiotic Analysis
Bibliographic record
Abstract
This semiotic analysis aimed to explicate the underlying concepts used by advertisers in promoting cosmetic products.This is also to signify how females are more concerned and sensitive about their beauty through analysing the language of advertisements.Also, this study aimed to reveal the extent to which the language employed by the advertisers exploits the whims and weaknesses of which people, mostly females, have with regards to beauty concepts.The linguistic corpora revealed that advertisers illuminate the concept of beauty by emphasizing the confidence and contentment women can get when they use the cosmetic product.With women as the target market, advertisers focus on enhancing the hegemonic qualities of women such as confidence and sex appeal.These concepts and qualities are made more sensitive to women to persuade female consumers that they can achieve anything they want for a limited price.Advertisers have communicated with female consumers by portraying their ideal selves, alongside with colours and slogans.One can see the value of conceptualizing the desires of people as object of attraction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".