تفعيل الشراكة بين القطاعين العام والخاص كآلية لتمويل مشروعات البنية التحتية في الجزائر على ضوء التجارب الناجحة لكل من مصر وكندا
Bibliographic record
Abstract
الملخص: تدخل الشراكة بين القطاع العام والقطاع الخاص في الاتجاهات الحديثة لتطوير القطاع الخاص وتعزيز مكانته في النشاط الاقتصادي، حيث تزايد عدد البلدان التي اختارت التوجه نحو الشراكة بين قطاعيها العام والخاص قصد فتح مجال آخر للتوسع في النشاط للقطاع الخاص ألا وهو قطاع البنى التحتية والخدمات المرتبطة به والذي تنفرد به عادة الدولة من خلال مؤسساتها العامة، وتعد كل من مصر و كندا من الدول التي قطعت أشواط متقدمة في مجال الشراكة بين القطاعين، وخاصة في المشاريع المشتركة مع القطاع الخاص في مجال البنية التحتية، وتهدف هذه الدراسة إلى تحليل هذين التجربتين وإبراز أهمية الاستفادة منهما في مجال تمويل مشروعات البنية التحتية في الجزائر. Abstract:The partnership between public sector and private sector is part of the recent trends in the development of the private sector and the strengthening of its position in economic activity. Number of countries that have chosen to move towards partnership between their public and private sectors in order to open up another area of expansion of private sector activity, namely the infrastructures and related services sector, which is monopolistic to the state through its public institutions.Egypt and Canada are among the advanced countries in the field of partnership between the two sectors, especially in joint projects with the private sector in the field of infrastructure. The aim of this study is to analyze these experiences and highlight the importance of benefiting from them in financing infrastructure projects in Algeria.Keywords: partnership, public sector, private sector, infrastructure, Egyptian experience, Canadian experience
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.271 | 0.239 |
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".