Socio-Economic and demographic consequences of migration in Kerala
Bibliographic record
Abstract
Migration has been the single most dynamic factor in the otherwise dreary development scenario of Kerala in the last quarter of the past century. Migration has contributed more to poverty alleviation and reduction in unemployment in Kerala than any other factor. As a result of migration, the proportion of population below the poverty line has declined by 12 per cent. The number of unemployed persons - estimated to be only about 13 lakhs in 1998 as against 37 lakhs reported by the Employment Exchanges - has come down by more than 30 per cent. Migration has caused nearly a million married women in Kerala to live away from their husbands. Most of these women, the so-called "Gulf wives" had experienced extreme loneliness to begin with; but they got increasingly burdened with added family responsibilities with the handling of which they had little acquaintance so long as their husbands were with them. But over a period of time, and with a helping hand from abroad over the ISD, most of them came out of their feeling of desolateness. Their sense of autonomy, independent status, management skills and experience in dealing with the world outside their homes - all developed the hard way - would remain with them for the rest of their lives for the benefit of their families and the society at large. In the longrun, the transformation of these one million women would have contributed more to the development of Kerala society than all the temporary euphoria created by foreign remittances and the acquisition of modern gadgetry. Kerala is becoming too much dependant on migration for employment, sustenance, housing, household amenities, institution building, and many other developmental activities. The inherent danger of such dependence is that migration could stop abruptly as was shown by the Kuwait war experience of 1990 with disastrous repercussions for the state. Understanding migration trends and instituting policies to maintain the flow of migration at an even keel is more important today than at any time in the past. Kerala workers seem to be losing out in the international competition for jobs in the Gulf market. Corrective policies are urgently needed to raise their competitive edge over workers in the competing countries in the South and the South East Asia. Like any other industry, migration needs periodic technological up-gradation of the workers. Otherwise, there is the danger that Kerala might lose the Gulf market forever. The core of the problem is the Kerala worker's inability to compete with expatriates from other South and South Asian countries. The solution naturally lies in equipping our workers with better general education and job training. This study suggests a two-fold approach - one with a long-term perspective and the other with a short-term perspective. In the short-run, the need is to improve the job skills of the prospective emigrant workers. This is better achieved through ad hoc training programmes focussed on the job market in the Gulf countries. In the long-run, the need is to restructure the whole educational system in the state taking into consideration the future demand for workers not only in Kerala but also in the potential destination countries all over the world, including the USA and other developed countries. Kerala emigrants need not always be construction workers in the Gulf countries; they could as well be software engineers in the developed countries. JEL Classification : J16, J21, J23 Key words : Kerala, emigration, return migration, remittances, gender, demography, elderly
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".