The Relationship Between the Use of Social Media and Cross-Cultural Competency Among International Students in Saudi Arabia
Bibliographic record
Abstract
This study investigates the role of social media in helping international students in Saudi Arabia develop cross-cultural competency. “International students” is a term that has vastly been perceived to describe students who study in the USA, Canada, and Europe. However, Saudi Arabia—one of the biggest Middle Eastern Countries—has successfully attracted over 50 thousand international students who represent 159 countries around the world to come and study in Saudi Arabia. This influx of students represents different cultural backgrounds. The study uses a survey that snowballed into potential participants, all of whom are international students in Saudi Arabia. A total number of 134 participants successfully completed the survey (of whom 121 are males). The study found that 113 participants gained cross-cultural competency, conditioning that they own social media accounts, spend some time daily on social media, and interact with global content. The study concludes that more research is needed on the population of international students in Saudi Arabia as this population deserves more research-focused attention. Keywords: International students, cross-cultural competency, social media, Saudi Arabia.
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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 | 0.001 | 0.003 |
| 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 | 0.000 | 0.001 |
| 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".