أثر استقطاب الموارد البشرية على الميزة التنافسية بالمدارس الخاصة
Bibliographic record
Abstract
تهدف هذه الدراسة إلى تحليل أثر استقطاب الموارد البشرية على تحقيق الميزة التنافسية في المدارس الخاصة العاملة في مصر، وذلك في ظل بيئة تعليمية تشهد تزايدًا ملحوظًا في حدة المنافسة، وتركز المدارس الخاصة بشكل متزايد على استقطاب كفاءات بشرية متميزة لضمان التفوق النوعي والخدمي. استخدمت الدراسة المنهج الوصفي التحليلي، وتم تطبيقها ميدانيًا على عينة من أصحاب القرار في ثلاث مدارس خاصة بإدارة المقطم التعليمية خلال الربع الأخير من عام 2024، اعتمدت الدراسة على بناء نموذج يربط بين المتغير المستقل (استقطاب الموارد البشرية) بأبعاده مثل: تحليل الاحتياجات، واستراتيجيات الجذب، وآليات الاختيار، والاحتفاظ، والالتزام بالمعايير، وبين المتغير التابع (الميزة التنافسية) بأبعاده: خفض التكلفة، والجودة، والإبداع، والمرونة، أظهرت نتائج التحليل الإحصائي وجود علاقة دالة إحصائيًا بين جودة الاستقطاب وتحقيق الميزة التنافسية، حيث تبين أن الاستقطاب الفعال يسهم في تقليل التكاليف وتحسين جودة الأداء التعليمي وزيادة الابتكار والمرونة في تقديم الخدمات. وقدمت الدراسة مجموعة من التوصيات أبرزها: ضرورة تطوير استراتيجيات استقطاب مرنة تتلاءم مع سوق العمل التعليمي، وتحسين بيئة العمل لجذب الكفاءات، والتركيز على التوظيف القائم على الكفاءة لا المجاملة. This study aims to analyze the impact of human resource recruitment on achieving competitive advantage in private schools operating in Egypt. This is in light of an educational environment witnessing a marked increase in the intensity of competition. Private schools are increasingly focusing on attracting distinguished human resources to ensure qualitative and service excellence. The study used a descriptive analytical approach and was applied in the field to a sample of decision-makers in three private schools in the Maadi Educational Administration during the last quarter of 2024. The study relied on constructing a model linking the independent variable (human resource recruitment) with its dimensions, such as needs analysis, attraction strategies, selection mechanisms, retention, and adherence to standards, with the dependent variable (competitive advantage) with its dimensions: cost reduction, quality, creativity, and flexibility. The results of the statistical analysis revealed a statistically significant relationship between the quality of recruitment and achieving competitive advantage, as it was shown that effective recruitment contributes to reducing costs, improving the quality of educational performance, and increasing innovation and flexibility in service provision. The study presented a set of recommendations, most notably: the need to develop flexible recruitment strategies that are compatible with the educational labor market, improve the work environment to attract talent, and focus on hiring based on competence rather than favoritism.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.420 | 0.432 |
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".