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