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Record W155286801

DOES REMITTANCES FINANCE WELFARE DEVELOPMENT?: EVIDENCE FROM THE SOUTH PACIFIC ISLAND NATION OF FIJI

2014· article· en· W155286801 on OpenAlexaboutno aff
Rukmani Gounder

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsEarningsNexus (standard)EconomicsWelfarePovertyForeign direct investmentDevelopment economicsLabour economicsEconomic growthFinanceMarket economy
DOInot available

Abstract

fetched live from OpenAlex

Remittances to developing nations have become an important source of income to finance the recipient households? livelihoods, where changes in expenditure patterns, consumption and savings-investment nexus for long term development lead to improve in wellbeing. The Pacific Islands have also seen to a significant rise in remittances and it has become a steady source of foreign exchange earnings. The island nations have a sizeable migration flow to Australia, New Zealand, the United States and United Kingdom as well as to other Pacific islands. A large number of emigrants from Fiji also migrate to Canada. More recently, remittances form a substantial flow through temporary labour schemes. Fiji?s rising migrant stock has seen remittances as the second largest foreign exchange earner after tourism surpassing other foreign capital flows of foreign aid, foreign direct investment as well as earnings from major commodity exports. It has large off-shore labour markets through specific employment abroad for teachers, nurses, care takers, sports personnel, military personnel and security officers in Australia, New Zealand, Dubai, United Kingdom, Middle East and the United Nations peace keeping force in the conflict-laden countries. The link between remittances and expenditure patterns has become an important nexus in the global welfare development framework. By increasing income of the recipient households?, remittances have gained impetus in the development agenda for its contribution to individual welfare through a range of consumption goods, entrepreneurial small and medium scale business and poverty reduction. Remittances impact on households? welfare shows that this financial inflow has been used for consumer durable and non-durable goods, food, housing, savings, investment and developing human capital, i.e., schooling and health outcomes. Its eventual developmental impact depends on the sustainability and what categories of consumption and innovative investment expenditures the households spend remittances on. This study examines the impact of remittances on welfare development in Fiji using the household income and expenditure survey 2002-03 dataset for 5, 245 households. Expenditure patterns of the households are estimated for various categories and further disaggregated by ethnicity, i.e. Fijian and Indo-Fijian households. The results provide some implications for social financing for wellbeing and note the empowering and visionary opportunities of remittances to be part of development.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.289
Threshold uncertainty score0.575

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.018
GPT teacher head0.257
Teacher spread0.239 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2014
Admission routes1
Has abstractyes

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