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Record W2766851266 · doi:10.1186/s12960-017-0249-5

Is there a financial incentive to immigrate? Examining of the health worker salary gap between India and popular destination countries

2017· article· en· W2766851266 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueHuman Resources for Health · 2017
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsSalaryIncentiveHealth administrationWork (physics)Health carePurchasing power parityPurchasing powerBusinessDemographic economicsEconomic growthEconomicsFinanceExchange rate

Abstract

fetched live from OpenAlex

BACKGROUND: International migration is one of the factors resulting in the shortage of Human Resources for Health (HRH) in India. Literature suggests that migration is fuelled by the prospect of higher salaries available abroad. The extent of these salary differentials are unknown, and this study seeks to examine the salaries of selected HRH in India and four popular destination countries (United States of America, United Kingdom, Canada and the United Arab Emirates), whilst accounting for the in-country cost of living. This study will therefore determine truer financial incentives for Indian HRH to migrate abroad. METHODS: A purchasing power parity (PPP) ratio is employed to equalise the international price of buying a representative basket of commonly bought goods (including food, entertainment, fuel and utilities). Using the PPP index, real differences in salaries are directly compared for selected work categories and different levels of work experience in the four respective countries. RESULTS: Nurses in the USA can earn up to 82.7% more than their Indian counterparts. Nurses in Canada and the UAE reveal more modest salary differentials, yet still significant better off by up to 28 and 20% respectively. Only nurses in the UK are potentially materially worse off than nurses working in India. We observe significant potential PPP gains of up to 57.4, 99.1 and 94.4% for medical doctors in the USA, Canada and the UAE respectively. Medical specialists potentially experience the greatest income disparities with anaesthetists potentially earning up to 600% more than their counterparts in India. Radiologists operating in the UK and general surgeons working in the USA can potentially earn more than double that of their counterparts working in India. We observe more modest positive or negligible PPP gains in other selected countries for health specialists. CONCLUSION: Even when considering the differences in the cost of living, the financial incentive for selected cadres of Indian HRH to seek work abroad remains strong. The migration of Indian HRH to countries offering superior salaries makes it difficult for India to retain experienced health personal and compromises government efforts to render health care more accessible across the country.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0080.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.101
GPT teacher head0.447
Teacher spread0.347 · 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