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Record W3187726888

COVID-19: Rebooting the Indian Economy?

2021· article· en· W3187726888 on OpenAlexaboutno aff
Abhilash Chandra

Bibliographic record

VenueSSRN Electronic Journal · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsPurchasing power parityWorld economyEconomicsEconomyLiberalizationChinaBalance of paymentsReal gross domestic productGlobalizationQuarter (Canadian coin)Development economicsGeographyPolitical scienceInternational economicsExchange rateMarket economy
DOInot available

Abstract

fetched live from OpenAlex

The Indian economy is considered as a Middle Income Developing Economy. It is the world's third-largest economy by Purchasing Power Parity (PPP) GDP and the sixth-largest by nominal. According to International Monetary Fund, India ranked 124th and 142nd by GDP (PPP) and GDP (nominal) respectively in 2020. In 1991 an acute balance of payments crisis and the end of the Cold War led to the adoption of a broad economic reform LPG (liberalization, privatization, and globalization) in India. The annual average GDP growth has been 6% to 7% since the 21st century. India was the world's fastest-growing major economy, surpassing China in four consecutive years 2014-2018. Historically, for most of the two millennia from the 1st until the 19th century, India was the largest economy in the world. India has been largely disruptive due to the economic impact of the 2020 coronavirus pandemic. India has seen a downfall of 3.1% growth in the fourth quarter of the fiscal year 2020. In 2020, India's partners were China, Germany, Hong Kong, Indonesia, Malaysia, Saudi Arabia, South Korea, Switzerland, and the United States.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.044
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.003
Scholarly communication0.0090.008
Open science0.0010.004
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0210.003

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 head0.029
GPT teacher head0.263
Teacher spread0.234 · 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
GenreCommentary

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

Citations2
Published2021
Admission routes1
Has abstractyes

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