An Examination of Social Networks on the Recruitment Process in the United Arab Emirates
Bibliographic record
Abstract
<p>This study evaluates the effects of social networks on the recruitment of professional staff to Ras Al Khaimah’s government and private sector within the United Arab Emirates (UAE). Questionnaires were administered to human resources employees who work at various levels of Ras Al Khaimah’s government and private sector. A quantitative methodology was utilized for this study. The paper conducted a factor analysis for dimension reduction on the findings of a questionnaire submitted to selected businesses with Ras Al Khaimah in the United Arab Emirates. Findings indicated 5 underlying factors driving answers to the 24 questions included on the questionnaire. These 5 factors were labeled as (1) general perception, (2) convenience, (3) reliability, (4) international recruitment and (5) branding and marketing. These 5 underlying factors indicated that relationships exist between the variables.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".