Publicidad y estereotipos de género en el siglo XXI. El caso de la marca AXE
Bibliographic record
Abstract
Esta investigación se enfoca en un estudio de caso que analiza los estereotipos de género que la marca AXE transmite en su publicidad. El objetivo es verificar si se ha producido una evolución positiva de estos ya que, tradicionalmente, es una marca que se ha distinguido por su naturaleza y contenido sexista. Para este estudio se optó por un análisis de contenido de carácter cualitativo y cuantitativo longitudinal a partir de una muestra de veinte spots emitidos en España y Latinoamérica entre 2000-2019. Apoyándonos en investigaciones previas se definió una ficha de análisis para obtener el grado de sexismo, los indicadores de estereotipos y roles de género transmitidos sus mensajes. Los resultados concluyen que, a pesar de mantener una cultura sexista, en los últimos años se percibe un cambio en el concepto creativo que permite vislumbrar una mejora en la representación y relación de igualdad entre hombres-mujeres.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".