Exploring Dropouts as Challenges in Higher Education in Nepal: A Comprehensive Review
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 purpose of this study is to analyse the dropout rate of campus level of students in Nepal. The researchers adopted the process of scientific review as a meta-synthesis to analyse the dropout rate of the campus level students. An in-depth archival analysis followed by an intensive review would be strategies adopted during the scientific review. Secondary data was gathered by searching Google for scholarly publications and articles published between 2001 and 2024. The students want part-time jobs during the study. Such opportunities are less common in Nepal. The research study revealed that Nepali students gave their first priority to Australia, Canada, the USA, and Europe for their higher studies. After finishing their studies, they desired to stay there due to their job security. They applied for green card and permanently stayed there. On the other hand, Nepal lost young and skilled manpower who stayed abroad as immigrants. The study reveals that government can prevent brain-drain by proving financial assistance and employment opportunities to bachelor’s level students. The Nepalese government should make appropriate policy to retain its young workforce. Otherwise, its adverse impact will be seen soon.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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