Analytical Study Of Cultural Differences And Sustainability Of Indian Students Going Abroad
Bibliographic record
Abstract
Background- An individual’s personality is influenced by both human nature and culture. The culture is usually introduced at birth, developed over time, and nurtured as they grow up. India is one of the most densely populated country known for rich culture and heritage. Indian students are moving overseas for higher studies as they are attracted by global professional opportunities and world-class universities to get their dream job and achieve better career prospects. ‘ Objective- The purpose of this study is to understand whether the Indian students are well equipped to adjust in the foreign environment despite of experiencing culture differences when they reach host country. Design- The cultural characteristics of individuals are described by Hofstede’s cultural dimension theory, which is a framework for cross-cultural communication, developed by Geert Hofstede (Hofstede (2011)). The three sample countries chosen for the study are USA, Australia and Canada based on the justification that maximum proportion of Indian students are going to these above-mentioned countries for pursuing their higher education. Method- This paper is based on secondary research and highlights the indicating factors which are sufficient for the sustainability of Indian students in host country. Result- The findings indicate that although Indian students do experience cultural differences but still, they are able to sustain in different cultural settings. Conclusion- The reason behind this sustenance is the cultural values which have been developed in Indians during childhood due to which it is not difficult for them to adjust in new settings.
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.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".