The co-constitution of regional politics and massive infrastructures in the Transaqua water project
Bibliographic record
Abstract
Large-scale water infrastructure projects have seen a sudden surge to the top of the political agenda in many countries as a means of addressing developmental goals at both national and regional levels, despite a decline in funding for these projects in the 1990s and 2000s. The Transaqua inter-basin water transfer (IBWT) project, a 2400 km-long canal aiming to connect the Lake Chad and Congo River basins, has been recently hailed by the Lake Chad basin countries, international and regional organizations, and the private sector as the most feasible solution to revitalize Lake Chad’s declining water levels. It has also started to reconfigure the regional politics of two of Africa’s largest basins. This article focuses on this case study and analyses how regional features shape Transaqua and how it simultaneously reconfigures regional politics. Based on concepts such as ‘region’, ‘regionalism’ and ‘regionalisation’ within the international relations discipline and applying mixed methods of discourse, document and media analysis, we show how the project is influencing regional dynamics, alliances and power relations in the Lake Chad and Congo River basins, and how the Transaqua discourse evolves along with regional features such as droughts, water abundance and regional insecurities, despite being in the planning stage.
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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 | 0.005 | 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 | 0.012 | 0.017 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".