Bibliographic record
Abstract
In this paper, we bring our individual and collective memories of Nepal to reflect upon how we imagine, remember, and perform the diasporic nationalism while living abroad. We argue that diasporic nationalism is often framed by the homeland's historical dimensions and through an imagined and identificatory relation to the homeland. In doing so, we bring our learning experiences during high school in Nepal and critically zero in on how these curriculums taught us only a single narrative of Nepal-India relation by grossly neglecting the other side of the narrative. To deconstruct such a grand narrative, we critically analyze the other side of the narrative, which reveals the Nepal-India relation as a 'paradox' between closeness and detachment. We discuss cross-border controversies in which the Indian hegemony of perpetuating colonial ideas overpowers Nepal through political and geopolitical intervention. We conclude the paper with our remarks to mitigate animosities and rebuild the fractured relationship between the two nations.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.037 |
| Scholarly communication | 0.012 | 0.016 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| 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".