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Record W2146148984

Managing international labour migration from India: Policies and perspectives

2008· article· en· W2146148984 on OpenAlexaboutno aff
S. K. Sasikumar, Zakir Hussain

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSustenancePromotion (chess)EmigrationLegislatureExpatriateDestinationsBusinessGovernment (linguistics)Political scienceEconomic growthDevelopment economicsEconomicsTourismLaw
DOInot available

Abstract

fetched live from OpenAlex

The paper addresses issues related to the promotion and sustenance of international labour migration from India on the one hand and protection of migrant workers on the other. It reveals that labour migration flows from India since 1990s have not only registered impressive growth in respect of the traditional destinations like the United States of America, the United Kingdom, Canada and the Gulf countries but also have diversified and expanded to newly emerging migrant destinations in continental Europe, Australasia, East Asia and South-East Asia. The paper observes that a pro-active migration policy framework will further cement these trends. The paper provides a detailed evaluation of the Emigration Act, 1983, the most important policy instrument governing the migration of Indian workers for overseas employment on a contractual basis. It argues that that the Act needs to be reoriented so that it provides a legislative basis for better protection and welfare of the migrants on the one hand and for the active promotion of international labour migration from India on the other. It notes that the Act needs to be modified to check the activities of the unscrupulous agents and to make it harder for agents to cheat Indian workers who are keen on migrating overseas for employment. The grievance redressal system must also be made more effective. It observes that apart from strengthening and reorienting the Emigration Act, the system to monitor its implementation should be strengthened. The paper further highlights the need for international labour migration policy to provide increasing emphasis to promotion and facilitation of external labour flows from India and not be limited only to regulating and protecting functions of the State.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.017
GPT teacher head0.281
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2008
Admission routes1
Has abstractyes

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