Citizens’ Reflection on Democracy and Disaster in Nepal in the Wake of the 2015 Earthquake
Bibliographic record
Abstract
On April 25, 2015, Nepal was hit by a massive earthquake. Thousands of lives were lost. Extensive damage to infrastructure and property was reported. Using 30 interviews, I firstly examine how the people survived in the early days of the disaster. Secondly, I discuss how the citizens of Nepal, perceived democracy as a political system that is still novel for them, in the aftermath of the crisis. The interviewees reflected on the government’s response to the earthquake. Evidently, the study highlights the disjuncture between the kinds of relief a democratic state is expected to provide for the citizens and the state’s actual response to the needs of the earthquake survivors. Nepal has adopted democracy since 1990, however, it has failed to deliver on its promises, and people are thus ambivalent about the system. However, in the final analysis, it becomes apparent that people are unwilling to revert back to the old autocratic system. The conclusions of the study compel one to consider certain social processes. What affects citizens’ expectations of their government in the aftermath of a major disaster is contingent upon how states have acted in normal times. The state’s response to disasters might be influenced by what citizens expect from the state in the first place, thus, leading to a self-fulfilling prophecy. Finally, a democratic society is preferred by most, and the only way for the government to be more robust is to compel the leaders to adhere to the laws and regulations and operate according: those who break the laws must be made accountable.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.012 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".