MétaCan
Menu
Back to cohort
Record W2345980393 · doi:10.1111/1468-2346.12599

Iran's policy towards the Houthis in Yemen: a limited return on a modest investment

2016· article· en· W2345980393 on OpenAlexaff
Thomas Juneau

Bibliographic record

VenueInternational Affairs · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMiddle East and Rwanda Conflicts
Canadian institutionsUniversity of OttawaGlobal Affairs Canada
Fundersnot available
KeywordsAlliancePoliticsSpanish Civil WarPolitical scienceGovernment (linguistics)Leverage (statistics)Proxy (statistics)Political instabilityDevelopment economicsEconomyPolitical economyEconomic historyLawHistoryEconomics

Abstract

fetched live from OpenAlex

For years, mounting instability had led many to predict the imminent collapse of Yemen. These forecasts became reality in 2014 as the country spiralled into civil war. The conflict pits an alliance of the Houthis, a northern socio-political movement that had been fighting the central government since 2004, alongside troops loyal to a former president, Ali Abdullah Saleh, against supporters and allies of the government overthrown by the Houthis in early 2015. The war became regionalized in March 2015 when a Saudi Arabia-led coalition of ten mostly Arab states launched a campaign of air strikes against the Houthis. According to Saudi Arabia, the Houthis are an Iranian proxy; they therefore frame the war as an effort to counter Iranian influence. This article will argue, however, that the Houthis are not Iranian proxies; Tehran's influence in Yemen is marginal. Iran's support for the Houthis has increased in recent years, but it remains low and is far from enough to significantly impact the balance of internal forces in Yemen. Looking ahead, it is unlikely that Iran will emerge as an important player in Yemeni affairs. Iran's interests in Yemen are limited, while the constraints on its ability to project power in the country are unlikely to be lifted. Tehran saw with the rise of the Houthis a low cost opportunity to gain some leverage in Yemen. It is unwilling, however, to invest larger amounts of resources. There is, as a result, only limited potential for Iran to further penetrate Yemen.

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)0.007
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: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0070.005
Open science0.0010.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0280.004

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 head0.054
GPT teacher head0.312
Teacher spread0.259 · 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

Citations136
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueInternational AffairsSame topicMiddle East and Rwanda ConflictsFrench-language works237,207