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Culturally Appropriate Web User Interface Design Study

2010· book-chapter· en· W2490781207 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.

Bibliographic record

VenueIGI Global eBooks · 2010
Typebook-chapter
Languageen
FieldComputer Science
TopicDigital Communication and Language
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsUsabilityUser interface designUser interfaceInterface (matter)Computer scienceWeb designUser experience designHuman–computer interactionGlobeWorld Wide WebCultural diversityUniversal designKnowledge managementThe InternetPsychologySociology

Abstract

fetched live from OpenAlex

A number of research studies support the importance of culturally appropriate design for e-business, e-commerce and advanced learning applications. This is not surprising, considering influence of user interface design on usability, accessibility and acceptability of software. To identify cultural preferences in visual interface design, the authors conducted research studying culture-specific web interface design elements for a large number of countries all over the globe. This chapter reports on study methodology and results, focusing mostly on the global colors study. The authors explain the approach and research methodology they utilized to conduct the automated “cultural audit” for identification of culture-relevant design and color preferences in web interface design. Research methodology for a manual “cultural audit” is also discussed. The authors present the overall findings of their study, and conclude with observations on the usefulness of their research approach, the applicability of cultural analysis tools the authors developed and future research in culturally appropriate user interfaces.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.666
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0030.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.028
GPT teacher head0.268
Teacher spread0.240 · 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