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Record W3088719061

The Constructed Lifestyle Image: An Examination of Mass Media, Online Social Influencers, and the Commodification of the Self

2020· article· en· W3088719061 on OpenAlexaff
Katherine Cao

Bibliographic record

VenueCrossings · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsStudioInfluencer marketingCommodificationBeautyAdvertisingSocial mediaSociologyConsumerismAestheticsBusinessVisual artsArtPolitical scienceMarketingComputer scienceWorld Wide WebEconomics
DOInot available

Abstract

fetched live from OpenAlex

In the ever-changing landscape of New-age social media, trendy and popular online influencers reign supreme as they vie for subscribers, followers, and the like through advancing methods of technological reproduction. “Village Studio,” an upscale photo studio disguised as a beautiful and pristine SoHo apartment, caters to the needs of on-the-rise online influencers looking to score brand deals through creating and curating images that contribute to a constructed self, eventually leading to cultural and monetary capital. Popular photo-based social media websites such as Instagram encourages any person with a smartphone and a camera to participate in such an environment of cultural one-upmanship, though it should be noted that this is a gendered phenomenon and the self-indulgent nature of sharing images of wealth, beauty, and lifestyle are viewed as predominantly female. Through examination of the Village Studio, new cultural forms are revealed and the images and marketing strategies of what has become an online industry are interrogated.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0030.007
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.017
GPT teacher head0.282
Teacher spread0.265 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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