Geo-Logics of Power: Disaster Capitalism, Himalayan Materialities, and the Geopolitical Economy of Reconstruction in Post-Earthquake Nepal
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The 2015 earthquakes in Nepal killed more than 9,000 people, displaced millions of people and deeply affected the economy. The earthquakes and reconstructions processes also transformed Nepal into a complex terrain of geoeconomic accumulation and geopolitical manoeuvring, including major international capital flows, the promulgation of a new constitution, an economic blockade by India and the expansion of trade corridors with China. Building on critiques of ‘disaster capitalism’, we propose and mobilize the concept of ‘geo-logics of power’ to draw further attention to the materialities of geopolitical and geoeconomic processes shaping reconstruction in post-earthquake Nepal. Focusing on two trans-Himalayan corridors connecting Nepal and China, we argue that the Nepal experienced a particular form of disaster capitalism: one in which the geo-logics of power – including trans-Himalayan discourses, practices, and materialities – came to shape political and economic transformations of a country long portrayed as a ‘buffer’ state between Indian and China. More broadly, we suggest that geo-logics of power result from a combination of geopolitical and geoeconomic power dynamics informed by geological formations and associated socio-natural processes.
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.
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 | 0.000 | 0.003 |
| 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 it