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Record W4378187927 · doi:10.29173/spectrum176

Whiteness as Beauty

2023· article· en· W4378187927 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueSpectrum · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMedia, Gender, and Advertising
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBeautyHierarchyAestheticsIdeal (ethics)White (mutation)Critical discourse analysisSociologyGender studiesArtPolitical sciencePolitics

Abstract

fetched live from OpenAlex

Do online shopping advertorials for whitening skincare products in South Korea perpetuate a racial hierarchy wherein whiteness is maintained as an ideal beauty standard? If so, how is this hierarchy articulated and reinforced with words and images? Whitening products, such as tone-up creams and sunscreens, have become increasingly prevalent in the skincare industry in South Korea. Adding a level of nuance to earlier research, my research undertakes a critical feminist discourse analysis method to examine 19 skincare advertorials on the South Korean beauty e-commerce site, Olive Young Global. This study breaks new ground by taking an inductive analysis approach to analyzing these advertorials to produce findings comparable to similar studies in other Asian countries. Thus, it works to confirm the overall message being communicated that these products are sold as the key to a woman’s quest for a white beauty ideal. By undertaking an inductive critical discourse analysis, the research will develop themes based on the exploration of these advertorials with some guidance from existing literature. The globalization of beauty promotes a falsely universal white(ned) woman, and this project evidences a nuanced analysis of the lexical choices and images employed to promote the idea that whiteness and youthfulness equate to “natural” beauty. This critical feminist discourse analysis will provide insight into how a racial hierarchy is reinforced through media and how the exclusion of racialized women from spaces intended to empower all women will reproduce the societal hierarchy among women within the beauty industry.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.553
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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.

Opus teacher head0.037
GPT teacher head0.354
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it