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Record W7027149255

Building on the Western Australian Boom: The Drivers and Shapers of India's Economic Development in the 21st Century

2007· other· en· W7027149255 on OpenAlexaboutno aff

Bibliographic record

VenueVictoria University Research Repository (Victoria University) · 2007
Typeother
Languageen
FieldArts and Humanities
TopicSchopenhauer and Stefan Zweig
Canadian institutionsnot available
Fundersnot available
KeywordsDiasporaOutsourcingReputationCapital (architecture)ImmigrationScale (ratio)Foreign direct investment
DOInot available

Abstract

fetched live from OpenAlex

Related to India's specific cultural base is the central role of the Indian diaspora in the nation's recent growth.The Indian diaspora is not only a source of capital transfers to India, but also has become increasingly influential in the establishment of export oriented high-tech IT and ITEB services in India.Large scale migration from India to England, Canada, and the USA started in the late 1950s and early 1960s -Australia joined these countries as a destination of Indian migrants in the mid to late 1970s.Over the years, while the numbers of such migrants from India have increased, the early migrants have also gained prominence in their adopted countries in business and commerce, medical profession, academia and IT industries.After the opening up of India's economy in the early 1990s, Indian diaspora has become increasingly active and influential in shaping the country's export drive.As a sign of this role is the high level of remittances from non-resident Indians -outstanding deposits have increased from US$13.7 billion in March 1991 to US$35.2 billion in March 2006.A recent study by the World Bank Institute highlighted the economic contribution of Indian diaspora when it noted: Riding the wave of growing reputation and visibility of Indians in the IT sector, many well-placed senior executives (of Indian origin) in big corporations who had moved to US, UK and Canada in the 1960s influenced outsourcing-related decisions in India's favour.As the networking and mentoring role of diaspora increases India will continue to retain the edge in outsourcing (Dahlman and Utz 2004). Growing Global Role of Indian FirmsIndia's firms are becoming global.Firms such as Reliance Industries, Tata Steel and Infosys are among the most efficient in the world.A television manufacturing firm Videocon was recently reported as the front-runner in a bid to take over Korean consumer goods giant Daewoo for $650 million.Indian firms acquired 76 foreign companies between January and June 2006 for $US5.2 billion.The purchases this year follow last year's shopping spree when Indian companies acquired stakes in 104 companies for $US3.5 billion, up from $US2.0 billion in 2004.Increasingly, Indian firms are also investing in R&D capacity.In 2004, Indian pharmaceutical firms filed around 200 patents.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score0.223

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0050.003
Scholarly communication0.0060.003
Open science0.0010.005
Research integrity0.0010.003
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 head0.040
GPT teacher head0.253
Teacher spread0.213 · 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 designNot applicable
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

Citations0
Published2007
Admission routes1
Has abstractyes

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