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Record W4316590749 · doi:10.1537/ase.220905

Comparing direct-to-consumer genetic testing services in English, Japanese, and Chinese websites

2023· article· en· W4316590749 on OpenAlexaff
Kentaro Nagai, Mikihito Tanaka, Alessandro R Marcon, Ryuma Shineha, Katsushi Tokunaga, Timothy Caulfield, Yasuko Takezawa

Bibliographic record

VenueAnthropological Science · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsUniversity of Alberta
FundersResearch Institute of Science and Technology for SocietyJapan Society for the Promotion of Science
KeywordsChinaBeautyEmpowermentAdvertisingEast AsiaMarketingPsychologyBusinessPolitical scienceEconomic growthEconomicsLaw

Abstract

fetched live from OpenAlex

Direct-to-consumer genetic testing (DTC-GT) has rapidly become available and affordable throughout developed countries. However, comparative research on DTC-GT services beyond Western countries has remained scarce, particularly in East Asian countries such as Japan and China. Hence, this study’s hypothesis is that although DTC-GT services in three languages might utilize the same underlying testing technology, such services are likely to represent the social, economic, and political characteristics of each country. For the study, a total of 267 websites (182 English, 32 Japanese, and 53 Chinese) were analyzed and coded reflexively into five categories for content analysis before interpretation using cluster and factor analyses. The results demonstrated variation between the three languages that reflected their respective consumer cultures: English, Chinese, and Japanese genetic testing websites focused on empowerment and ancestry; cultural values, especially familism; and health and beauty, respectively.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

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

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 head0.024
GPT teacher head0.318
Teacher spread0.293 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations5
Published2023
Admission routes1
Has abstractyes

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