GERD, a Path, or Hindrance toward SDG 6.5 in the Nile River Basin?
Bibliographic record
Abstract
This paper explores the possibility of achieving SDG 6.5 by 2030 in the Nile Basin by exploring the hydro-politics between the three main riparian states, Egypt, Ethiopia, and Sudan. Through a literature review of relevant sources, it is ascertained that, historically, Egypt has maintained a hegemonic control of the Nile through disputed treaties negotiated by Great Britain. However, the state-financed construction of the Grand Ethiopian Renaissance Dam (GERD) has the potential to shift this hegemonic control of the Nile Basin in favour of Ethiopia. While this construction may act as a source of political tension and low-scale conflict in the region, this paper critically examines how the implementation of a sustainable dam filling rate, Integrated Water Resource Management (IWRM), and the Nile Basin Initiative (NBI) can foster transboundary water cooperation between the three major players. In line with previous research, we argue that the GERD’s main effect is mostly positive, especially if the three main riparian states are actively cooperating and are considering advice from the scientific community.
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 | 0.006 | 0.005 |
| 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 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".