Bibliographic record
Abstract
The study investigates how online social networks’ users in two Arab countries are concerned about their online privacy. A structured questionnaire was used to collect data from a sample (N=325) of Arab respondents in Emirates and Egypt. The results reveal a negative correlation between online privacy concerns and respondents' likelihood of providing personal information. Females are found to be more concerned about their privacy than males. Also, they tend to be more concerned than males in taking actions that protect their privacy. Emiratis use less online social networks than Egyptians and Arab residents in the UAE, while Egyptians have greater trust in online social networks. Key words: Online privacy concerns; Online social networks; Trust in online social networks; Privacy protection and Communication Privacy Management theoryResume: L'etude examine comment les utilisateurs des reseaux sociaux en ligne dans deux pays arabes sont preoccupes par leurs affaires personnelles en ligne. Un questionnaire structure a ete utilise pour recueillir des donnees aupres d'un echantillon (N = 325) des repondants dans les Emirats arabes et l'Egypte. Les resultats revelent une correlation negative entre la preoccupation sur la vie privee et la probabilite des repondants de fournir des renseignements personnels en ligne. Les femmes sont plus preoccupees par leur vie privee que les hommes. En outre, elles ont plus de tendance que les hommes a prendre des mesures qui protegent leur vie privee. Les Emiratis utilisent moins les reseaux sociaux en ligne que les Egyptiens et les residents arabes des Emirats Arabes Unis, tandis que les Egyptiens ont une plus grande confiance en reseaux sociaux en ligne.Mots-cles: problemes concernant la vie privee en ligne; reseaux sociaux en ligne; confiance en reseaux sociaux; protection de la vie privee et la theorie de la gestion des affaires personnelles dans la communication
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".