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Record W4245557108 · doi:10.1108/oxan-db208410

Recession increases risks to Russian leadership

2016· other· en· W4245557108 on OpenAlexaboutno aff

Bibliographic record

VenueEmerald expert briefings · 2016
Typeother
Languageen
FieldSocial Sciences
TopicRussia and Soviet political economy
Canadian institutionsnot available
Fundersnot available
KeywordsInflation (cosmology)SanctionsRecessionEconomicsCurrencyMonetary economicsRussian economyCapital (architecture)Exchange rateCentral bankQuarter (Canadian coin)Foreign capitalFlaggingEconomic policyMonetary policyForeign direct investmentMacroeconomicsPolitical scienceEconomic system

Abstract

fetched live from OpenAlex

Significance Recovery will be slower in 2017 than previously estimated, at 0.9% instead of 1.7%, the bank said. The low price of oil is the main burden on the flagging Russian economy. Moreover, high inflation due to the weak ruble will prevent the Central Bank of Russia (CBR) from lowering its benchmark rate from the current 11% before the fourth quarter of 2016. Impacts Protracted economic turmoil could translate into street protests, the first challenge Putin has faced since the 2011 election. State intervention in the economy will increase given the weakness of investor funding and domestic capital markets. Unless Western sanctions are lifted in 2016, a return to a growth trajectory is unlikely. Foreign currency reserves may run low by mid-2017 unless the economy recovers.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.492
Threshold uncertainty score1.000

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0540.005

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 head0.122
GPT teacher head0.393
Teacher spread0.270 · 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; both teacher heads agree on what is shown here.

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
Published2016
Admission routes1
Has abstractyes

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