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Record W4403093157 · doi:10.38204/komversal.v6i2.2052

Konstruksi Makna Terkait Country Of Origin Brand Skintific Pada Komunitas Siber “X”

2024· article· en· W4403093157 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueKOMVERSAL · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics and Language Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsBusiness

Abstract

fetched live from OpenAlex

In 2023, there was a heated discussion regarding the issue that Skintific is not actually a product from Canada, despite its claim of being "Formulated in Canada," but is instead made in China. This issue gained traction on social media, particularly on X/Twitter, prompting a wide range of responses. This research was conducted to understand the meanings attributed by the X cyber community to the brand's country of origin. The study used netnography to deconstruct the norms influencing the decision-making of the group under study. Although some consumers were confused about the product's country of origin, this did not diminish their satisfaction with the product's effects on their skin. However, the majority of the online community expressed skepticism about the "Formulated in Canada" claim, which led to distrust, as the product is actually made in China. This was seen as a misleading marketing practice, resulting in dissatisfaction and disappointment among consumers.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.881
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.000

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 head0.016
GPT teacher head0.234
Teacher spread0.218 · 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