Investigating the Design of Arabic Web Interfaces Using Hofstede’s Cultural Dimensions: A Case Study of Government Web Portals
Bibliographic record
Abstract
This study examines the design characteristics of Web interfaces from Arab countries using Hofstede’s cultural dimensions. Organizational and graphical elements on a sample of 15 home pages of government Web portals are examined using content analysis. Element frequency scores were correlated with Hofstede’s dimensions and interpreted based on Marcus and Gould’s (2000) study. The results suggest that Hofstede’s model of culture does not fully reflect the design characteristics of Arabic interfaces.Cette étude examine les caractéristiques d'interfaces web de pays arabes au moyen des dimensions culturelles de Hofstede. Les éléments organisationnels et graphiques d'un échantillon de 15 pages d'accueil de portails gouvernementaux sont étudiés dans le cadre d'une analyse de contenu. Les scores de fréquence des éléments sont mis en corrélation avec les dimensions de Hofstede et interprétés en fonction de l'étude de Marcus et Gould (2000). Les résultats suggèrent que le modèle culturel de Hofstede ne reflète pas pleinement les caractéristiques des interfaces en arabe.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".