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Record W4285404596 · doi:10.1017/irn.2021.65

Marche Triomphale: A Forgotten Musical Tract in Qajar-European Encounters

2022· article· en· W4285404596 on OpenAlexaboutno aff
Mohsen Mohammadi

Bibliographic record

VenueIranian Studies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Studies and History
Canadian institutionsnot available
Fundersnot available
KeywordsStyle (visual arts)MusicalRace (biology)Quarter (Canadian coin)HistoryClassicsArtArt historyLiteratureSociologyGender studiesArchaeology

Abstract

fetched live from OpenAlex

Abstract This article introduces Julius Heise’s Marche Triomphale which reveals a history that was eliminated during the nineteenth century race theory publications. Beginning with an account of Iranians’ encounters with European military music, this article provides a brief history of Iranian military bands in European style, or the bands of muzikānchiān. It then addresses racial motivations behind a short account on Iranian music in 1885 by Victor Advielle, a French administrator. Arthur de Gobineau’s race theories were fashionable in nineteenth century Europe, and Victor Advielle used his fellow Artesian, Alfred Lemaire, to prove their racial superiority. Through Advielle’s account, Lemaire became the main figure of European music in Iran in the last quarter of the nineteenth century. The article proceeds with biographical information on two European musicians, Marco Brambilla (d.1867 in Tehran) and Julius Heise (d.1870 in Tehran), and uncovers the earliest known piece published for the bands of muzikānchiān: Marche Triomphale, À Sa Majesté Impériale Nassir-Ed-Din Shah Kadjar de Perse.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.009
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.011
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.066
GPT teacher head0.331
Teacher spread0.265 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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