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Record W4231150122 · doi:10.1108/oxan-db253134

India’s Gulf ties will face setbacks in the near term

2020· other· en· W4231150122 on OpenAlexaboutno aff

Bibliographic record

VenueEmerald expert briefings · 2020
Typeother
Languageen
FieldSocial Sciences
TopicMiddle East and Rwanda Conflicts
Canadian institutionsnot available
Fundersnot available
KeywordsMiddle EastFace (sociological concept)Investment (military)Development economicsCoronavirus disease 2019 (COVID-19)South asiaGeographyPolitical scienceChinaPandemicEconomic growthEconomyBusinessHistoryAncient historyEconomicsSociologyMedicinePolitics

Abstract

fetched live from OpenAlex

Significance Indian nationals are struggling to maintain jobs in the Middle East as GCC states contend with historically low oil prices as well as the economic fallout of the pandemic. Gulf countries have meanwhile expressed concern at what they regard as growing anti-Muslim sentiment in India. Impacts Pakistan will step up efforts to gather support from GCC countries regarding the Kashmir issue. Saudi Arabia and the United Arab Emirates will increase investment in India’s health and tech sectors. The number of Indian migrant workers in South-east Asia, Australia and Canada will gradually increase.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.133
Threshold uncertainty score0.996

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.023
GPT teacher head0.288
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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2020
Admission routes1
Has abstractyes

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