A Cultural Analytic Study of Facial Imagery in Time Magazine, 1923–2014
Bibliographic record
Abstract
We extracted and categorized images of human faces from a digitized Time magazine archive of issues published from 1923 to 2014. The data revealed several large-scale trends that are consistent with the historical context of the magazine. We found that faces are more likely to be smiling in the context of advertisements compared to other contexts, that women are more likely to be smiling than men in all contexts, and that women’s faces are more likely to be found in advertisements than men’s faces. We observed trends in the presence of racialized faces: African American faces increased more or less linearly, reaching approximately proportional representation at the turn of the twenty-first century, while the appearance of faces categorized as Asian peaked in 1970. We interpret these trends through a theoretical framework that connects them to larger events in American history.   Nous avons extrait et catégorisé des images de visages humains à partir des archives numérisées du magazine Time, dont les numéros ont été publiés entre 1923 et 2014. Les données ont révélé plusieurs tendances à grande échelle qui sont cohérentes avec le contexte historique du magazine. Nous avons constaté que les visages sont plus susceptibles d'être souriants dans le contexte des publicités que dans d'autres contextes, que les femmes sont plus susceptibles d'être souriantes que les hommes dans tous les contextes, et que les visages de femmes sont plus susceptibles d'être trouvés dans les publicités que les visages d'hommes. Nous avons observé des tendances dans la présence de visages racialisés : Les visages afro-américains ont augmenté plus ou moins linéairement, atteignant une représentation approximativement proportionnelle au tournant du XXIe siècle, tandis que l'apparition de visages catégorisés comme asiatiques a atteint son maximum en 1970. Nous interprétons ces tendances à l'aide d'un cadre théorique qui les relie à des événements plus importants de l'histoire américaine.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.003 |
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 teacher head, 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".