Age transcended: A semiotic and rhetorical analysis of the discourse of agelessness in North American anti-aging skin care advertisements
Bibliographic record
Abstract
Drawing from a collection of over 160 North American print advertisements for anti-aging skin care products from January to December of 2009, this paper examines the discourse of agelessness, a vision of esthetic perfection and optimal health that is continually referred to by gerontologists, cultural theorists, and scientific researchers as a state of being to which humankind can aspire. Employing critical discourse analysis through the use of semiotics and visual rhetoric, this paper explores the means through which anti-aging skin care advertisements present to their viewers a particular object of desire, looking, more specifically, at how agelessness is presented as a way out and ultimate transcendence of age. Through the analytical tools of semiotics and visual rhetoric, four visions of agelessness are identified and explored in this paper: Agelessness as Scientific Purity, Agelessness as Genetic Impulse, Agelessness as Nature's Essence, and Agelessness as Myth. Whether found in the heights of scientific purity, the inner core of our genetic impulse, the depths of nature's essence, or whether agelessness itself has reached its own, untouchable, mythic status, the advertisements in this study represent one of the most pervasive vehicles through which our current vision(s) of ageless perfection are reflected, reinforced, and suspended in a drop of cream.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.014 | 0.035 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".