Public Private Partnership - vägen mot en effektiv hållbar utveckling?
Bibliographic record
Abstract
Our climate is a common responsibility for all countries. The European Investment Bank is playing a big role by regularly providing sub Saharan countries with financial resources so that they can take part of the work for a sustainable environment. Being the world's largest donor entails a great responsibility to act efficiently. This essay aims to investigate how the European Investment Bank uses the financial instrument PPP (Public Private Partnership). The essay aims to focus primarily on the effectiveness of the financial instrument and how it is being used through the African Infrastructure Fund on a project level. In order to analyzing this matter, a comparative case study will be done focusing on two projects. Lake Turkana Wind Power located in Kenya and Ruzizi III PPP which is a project for hydroelectric in Rwanda, Burundi and Congo. In order to obtain a result the investigation uses the theoretical framework aid conditionality, throughput- and output legitimacy to analyze the effectiveness and the quality of these projects. The result estimates that Ruzizi III is delayed due to disagreements between the three governments and private actors. Also, the work is made even more difficult by the political instability prevailing in these countries. Lake Turkana on the other hand is located in a comparatively more politically stable country where it has been easier to reach consensus since it is only one government and fewer actors involved. Shown from our results it is easier for parties to reach consensus if the state is politically stable and has knowledge about the functioning of the PPP. If the PPP strategy are being applied properly it will improve the effectiveness of the aid and therefore make a contribution to our environment.
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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) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.010 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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; both teacher heads agree on what is shown here.
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".