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Record W2040790107 · doi:10.1177/0276146713511464

<i>My Iranian Road Trip</i> – Comments and Reflections on Videographic Interpretations of Iran’s Political Economy and Marketing System

2013· article· en· W2040790107 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Macromarketing · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Studies and History
Canadian institutionsYork University
Fundersnot available
KeywordsRepresentativeness heuristicMacromarketingPoliticsExtant taxonMarketingEconomySociologyEconomicsPolitical scienceBusinessLawPsychologySocial psychology

Abstract

fetched live from OpenAlex

Iran is an enigmatic political economy and marketing system. Access to it for purposes of rigorous and thorough research is not easy. Scholars therefore must be creative when studying such systems, and may be limited to interpreting extant findings by others. In this article, the authors share comments and reflections on My Iranian Road Trip, a short film documenting Nicholas Kristof’s 2012 tour through Iran, and an ensuing panel that analyzed and discussed the film during the 39 th Annual Macromarketing Conference. The film was sponsored and released online by The New York Times. While it was agreed that some glimpse of Iran is better than none – and that Kristof’s film does contribute to the discourse on political and economic dynamics in Iran – the authors share comments on methodological shortcomings, representativeness, over-simplification, and concerns about some questionable conclusions, which inevitably implies need for more rigorous, thorough and nuanced research if we are to understand Iran’s complex political economy and marketing system.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.346
Threshold uncertainty score0.501

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.297
Teacher spread0.275 · 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