On the Migration Decision of Indian IT-Graduates: An Empirical Analysis
Bibliographic record
Abstract
Research hypotheses from various migration-theory approaches are tested through a study focusing on a sample of 1, 560 IT university students in India, just prior to the completion of their studies. The representative survey was conducted across India during the summer of 2003. The effect of economic and socio-political factors on the students’ willingness to migrate was examined by using variance analysis. The results show, on the one hand, a generally high willingness among those surveyed to migrate to industrialised countries, but on the other hand, a substantial number of IT-students want to stay in their home country, India. Economic factors tend to play a much greater role on their migration decisions, rather than say the sending or receiving country’s institutional or socio-political aspects. The significance test of individual factors shows that economic as well as institutional considerations; such as good career opportunities, a high income, and a high living standard, are considerably more important than other socio-political as well as institutional factors. Indian IT graduates evaluated better career opportunities much higher in their home country as compared to other locations. In an explicit location comparison of Germany with India and the United States/Canada - the classic immigration countries - as one of the potential host countries, the respondents rated only language/culture significantly higher for the United States/Canada than for Germany. The remaining economic and socio-political factors were rated higher for USA/Canada but do not show any significant differences between Germany, India, and USA/Canada. Interestingly, a location comparison of India with Germany and United States/Canada shows that IT graduates evaluated (salary, career opportunity, self employment, language/culture and social networks) significantly higher for their native country than for Germany and United States/Canada. Hence, in an international competition for skilled labour/best IT specialists, India has also emerged as an attractive location. ZUSAMMENFASSUNG - (MZur Bewertung der Migrationsentscheidung von IT-Hochschulabsolventen aus Indien: Eine Empirische Untersuchung) Wir testen Forschungshypothesen aus migrationtheoretischen Ansätzen anhand einer Stichprobe von 1, 560 kurz von dem Studienabschluss stehenden IT-Hochschulabsolventen aus Indien. Die repräsentative Befragung wurde im Sommer 2003 landesweit in Indien durchgeführt. Mit Hilfe der Varianzanalyse wird die Wirkung der ökonomischen sowie gesellschaftspolitischen Einflussfaktoren auf die Migrationbereitschaft der Hochschulabsolventen unter-sucht. Die Ergebnisse zeigen einerseits eine hohe generelle Migration-bereitschaft der indischen IT-Absolventen in Industrieländer. Andererseits ist aber das Verbleiben in ihrem Heimatland Indien eine starke Alternative. Ökonomische Gründe spielen generell für die Migrationentscheidung eine viel wichtigere Rolle als andere institutionelle oder gesellschaftspolitische Aspekte im Herkunfts- und Empfängerland. Der Signifikanztest der einzelnen Einflussfaktoren bestätigt, dass ökonomische Gründe wie gute Karrieremöglich-keiten, hohes Einkommen und besserer Lebensstandard bei allen Empfänger-ländern signifikant wichtiger sind als die gesellschaftspolitischen Determinanten (wie Ausländerfeindlichkeiten, Aufenthalterlaubnis, Sprache und Soziale Netzwerke). Indische IT-Hochschulabsolventen bewerten gute Karrieremöglich-keiten höher in Ihrem Heimland als bei allen Empfängerländern. Bei einem konkreten Standortvergleich zwischen Deutschland, Indien und dem klassischen Immigrationsland USA bewerten die Befragten die Determinanten (wie Soziale Netzwerke, Karrieremöglichkeiten, Möglichkeit der Selbstständig-keit, das Gehalt und Sprache) signifikant wichtiger für Ihr Heimatland als für die USA und Deutschland. Im Wettbewerb um die besten IT-Experten ist Indien im Vergleich zu Nordamerikanischen Ländern und Deutschland ebenfalls ein attraktiver Standort.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".