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Record W4214828329 · doi:10.5089/9781475583076.002

Islamic Republic of Iran: 2016 Article IV Consultation-Press Release; Staff Report; and Statement by the Executive Director for the Islamic Republic of Iran

2017· article· en· W4214828329 on OpenAlexaboutno aff
International Monetary Fund

Bibliographic record

VenueIMF Staff Country Reports · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Sanctions and International Relations
Canadian institutionsnot available
Fundersnot available
KeywordsIslamIslamic republicRecessionInvestment (military)AccountingQuarter (Canadian coin)EconomicsBusinessPolitical scienceLawMacroeconomicsHistoryPolitics

Abstract

fetched live from OpenAlex

This 2016 Article IV Consultation highlights a rebound in economic growth in the Islamic Republic of Iran over the course of 2016–17 based on higher oil production. Real GDP grew 7.4 percent in the first half of 2016–17, rebounding from the 2015–16 recession. However, growth in the non-oil sector averaged 0.9 percent, despite having picked up in the second quarter, reflecting continued difficulties in access to financing and domestic financial sector and structural weaknesses. Growth is projected to stabilize at 4.5 percent over the medium term as the recovery broadens. The current account is forecast to remain in surplus as higher exports offset the pickup in imports related to investment.

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)0.004
metaresearch head score (Gemma)0.016
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.077
Threshold uncertainty score0.196

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0040.002
Open science0.0010.001
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0590.028

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 head0.033
GPT teacher head0.270
Teacher spread0.237 · 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
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

Citations4
Published2017
Admission routes1
Has abstractyes

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