Bibliographic record
Abstract
In this article I turn my attention to two hydropower plants, HPP Dabar and HPP Nevesinje, part of the massive Upper Horizons scheme, which is currently the largest infrastructural project in Bosnia and Herzegovina. Built by the China Energy Gezhouba and financed through a large loan from the Export–Import Bank of China, the enterprise forms a part of China’s Belt and Road Initiative, an unprecedented global development programme that involves nearly half of the world’s countries. The project is being built on the Zalomka, one of the largest sinking rivers in Bosnia and Herzegovina and the world, and its potential impacts are hotly debated and may be extremely far reaching. As Rob Nixon has argued, the mega-dam projects in many postcolonial nations have ‘depended’ on both physical structure and metaphorical discourse on ‘submergence’: of ‘disposable people and ecosystems, but also on the submerged structures of dependence that lay beneath the flamboyant engineering miracles’ (2011: 167). Drawing on these reflections and insights from the energy humanities, blue humanities and infrastructure studies, I consider dams as concretizations that ‘harness, produce, materialise, and symbolise’ (neo)colonial power relations (Max Haiven (2013) ‘The dammed of the Earth: Reading the mega-dam for the political unconscious of globalization’, in Cecilia Chen, Janine MacLeod and Astrida Neimanis (eds) Thinking with Water, Montreal: McGill-Queen’s University Press). Thus, from this perspective, this infrastructural project could be seen not only as ‘Chinese invasion’ through the Belt and Road Initiative, but also an invasion of nature by the nation state, often constituted as the necessary means to pursue a view of national and regional integration towards globalized modernity. Finally, I discuss an invasion of the dominant narrative by resistance, turning attention to the anti-damming intersectional and coalitional work in the Balkans, which includes protests, marches, forums, artistic interventions, and legal pressure aimed at stopping both local and the Chinese state-owned companies from dredging and blocking the rivers. Intervening in the normalized view of the extractive zone – the article argues – these acts of resistance form part of a broad struggle against what the anthropologist Anne Spice calls ‘invasive infrastructures’ (2018) that numerous communities are fighting against in the region (‘Fighting invasive infrastructures’, Environment and Society 9: 40–56).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.042 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".