The Great Green Wall in Senegal: questioning the idea of acceleration through the conflicting temporalities of politics and nature among the Sahelian populations
Bibliographic record
Abstract
In January 2021, the Great Green Wall Accelerator was announced at the third One Planet Summit in Paris. Based on the notion of acceleration developed by Harmut Rosa and using the idea of conflicting temporalities in the study of social-ecological systems, this article analyzes how the political will to accelerate the Great Green Wall reveals power dynamics between Western and Sahelian countries. We put in tension this acceleration of the Great Green Wall with (1) temporalities with respect to nature and reforestation, and (2) temporalities of life among the Sahelian populations. Whereas our contribution is mostly theoretical, building on Hartmut Rosa’s work, we illustrate our approach in terms of political ecology and anthropology based on an empirical case study of the Ferlo region in Senegal, a key region with respect to the Great Green Wall initiative. Our analysis shows that by controlling the temporality of the Great Green Wall program through this Accelerator, Western powers dominate the Sahelian states, making the Accelerator part of a neo-colonial approach. Moreover, the desire to accelerate the Great Green Wall with a massive investment in a short span of time corresponds to the perception of a nature made available, incompatible with the time of ecological restoration. Finally, the acceleration advocated by Western economic liberalism seems to be coming up against resistance of local populations rooted in an identity that values community solidarity, the stability of social structures, and closeness between humans, their herds, and nature.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".