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Record W3092628465 · doi:10.35632/ajis.v23i1.1641

Iran, Iraq, and the Legacies of War

2006· article· en· W3092628465 on OpenAlexaff
Louise Gormley, David Armani

Bibliographic record

VenueAmerican Journal of Islam and Society · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicPolitics and Conflicts in Afghanistan, Pakistan, and Middle East
Canadian institutionsImmersion (Canada)University of Toronto
Fundersnot available
KeywordsPresidencyPoliticsSacrificePersianMiddle EastSpanish Civil WarLawHistoryAncient historyWhite (mutation)Economic historyPolitical scienceTheologyPhilosophyArchaeology

Abstract

fetched live from OpenAlex

With the noble aims of conflict resolution and peace building, Lawrence G.Potter and Gary G. Sick have compiled an excellent collection of essays on“the war without winners” (p. 2). This remarkable publication, Iran, Iraq,and the Legacies of War, adds to Potter and Sick’s series of co-edited bookson Middle Eastern issues, namely, The Persian Gulf at the Millennium:Essays in Politics, Economy, Security, and Religion (Palgrave Macmillan:1997) and Security in the Persian Gulf: Origins, Obstacles, and the Searchfor Consensus (Palgrave Macmillan: 2002). Potter and Sick are two prominentscholars of international affairs at Columbia University. During theCarter presidency, Sick served as the principal White House aide for Iran onthe National Security Council. (Sick is well-known for his exposé All FallDown: America’s Tragic Encounter with Iran [Random House: 1985]).This 224-page book was written in the cautiously hopeful belief thatthe time has come for reconciliation to begin. It contains nine chapters plusPotter and Sick’s helpful introduction, which contextualizes the futile warthat shook the world. The Iran-Iraq war was one of the longest and costliestconventional wars of the twentieth century. Although the number ofcasualties is still in dispute, an estimated 400,000 were killed and perhaps700,000 were wounded on both sides (p. 2). The Economist commentedthat “this was a war that should never have been fought … neither sidegained a thing, except the saving of its own regime. And neither regime wasworth the sacrifice” (p. 2) ...

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.007
Scholarly communication0.0070.005
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.008
GPT teacher head0.253
Teacher spread0.246 · 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 designQualitative
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

Citations1
Published2006
Admission routes1
Has abstractyes

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