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Record W2107264685 · doi:10.1080/00210862.2011.524491

The Modernization of Iran and the Development of the Persian Carpet Industry: The Neo-Classical Era in the Persian Carpet Industry, 1925–45

2010· article· en· W2107264685 on OpenAlexaff
Martin Rudner

Bibliographic record

VenueIranian Studies · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Studies and History
Canadian institutionsCarleton University
Fundersnot available
KeywordsModernization theoryElitePersianThe artsGovernment (linguistics)Administration (probate law)Corporate governanceAncient historyIndustrial RevolutionPolitical scienceEconomic historyEconomyHistoryLawPoliticsManagementEconomics

Abstract

fetched live from OpenAlex

The two decades, 1925–45, witnessed a dramatic transformation and revitalization of the Persian carpet industry in response to developments in Iranian governance, society and economy. Two historical watersheds were covered by that period, notably the replacement of the Qajar dynasty by a modernizing administration under Reza Shah Pahlavi, and the subsequent wartime occupation of Iran jointly by the Soviet Union and Great Britain. It was during those two decades that Iran acquired a centralized system of government and the beginnings of a modern industrial base. The accompanying social transformation brought about the emergence of new classes of administrators and managers who constituted the dominant elite of the Reza Shah era. This twin process of centralization and modernization had a telling impact on Iranian culture and the arts, including the carpet arts.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.007
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.039
GPT teacher head0.299
Teacher spread0.261 · 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

Citations6
Published2010
Admission routes1
Has abstractyes

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