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Record W2583379612 · doi:10.20381/ruor-242

The Harper Administration’s Securitization of Iran

2016· article· en· W2583379612 on OpenAlexaboutno aff
Soha Masaeli

Bibliographic record

VenueuO Research (University of Ottawa) · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Relations and Foreign Policy
Canadian institutionsnot available
Fundersnot available
KeywordsSecuritizationAdministration (probate law)Political scienceBusinessFinanceLaw

Abstract

fetched live from OpenAlex

Despite Iran’s hostile relations with the West since the Islamic Revolution in 1979, Canada had often played the role of an honest broker and maintained relations with Iran, contrary to the US. Although the Canadian Government has always viewed the Islamic Regime as hostile, it was interested in pursuing diplomacy and other means to pressure Iran in areas such as human rights violations. This approach to dealing with Iran was altered and moved towards securitization after 2006, with the election of Prime Minister Stephen Harper. This paper will examine the securitization theory and apply it to the Harper administration’s approach to Iran, leading up to the final securitized moment of the closure of the Canadian embassy in Tehran and the expulsion of Iranian diplomats from Ottawa in 2012. This paper will then analyze the reasons that the Canadian Government provided for pursuing this decision. Ultimately, the research will present the argument that Prime Minister Stephen Harper’s identification of Iran as the biggest threat to global peace and security was an exaggeration of the real level of threat that Iran actually posed. This inflated level of threat may have had many causes, but chief among them was the Prime Minister’s personal convictions and relations with Israel and his foreign affairs policy approach which discouraged him from communicating with states or entities that were categorized as bad. Although this decision did not have any devastating effects on Canada, given that relations with Iran were always limited, it also did not achieve any desirable outcomes. In addition, various components of this securitizing move, such as listing Iran as a state sponsor of terrorism, have rendered any decision by future governments to reinstall relations with Iran difficult.

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)0.003
metaresearch head score (Gemma)0.006
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: Other · Consensus signal: none
Teacher disagreement score0.744
Threshold uncertainty score0.515

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0200.017
Scholarly communication0.0080.001
Open science0.0010.002
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.073
GPT teacher head0.376
Teacher spread0.303 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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