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Record W4410045646 · doi:10.21071/mijtk.v10i.16684

« Excessive Storytelling »: Seetzen as a Protagonist in the Postmodern Adventure Novel Empty Quarter – Rub ’al-Khali (1996) by Michael Roes

2025· article· en· W4410045646 on OpenAlexaboutno aff
Christoph Schmitt-Maaß

Bibliographic record

VenueMediterranea International Journal on the Transfer of Knowledge · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicNarrative Theory and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsAdventurePostmodernismStorytellingArtQuarter (Canadian coin)LiteratureVisual artsArt historyNarrativeAestheticsHistoryArchaeology

Abstract

fetched live from OpenAlex

In his novel Empty Quarter – Rub ’al-Khali, published in 1996, Berlin writer Michael Roes tells of a fictional traveller to the Orient, Ferdinand Alois Schnittke, who is searching for Moses’s Tablets of the Law in the late eighteenth century. The reflections of the nameless, first-person narrator living in Yemen serve as a contrafaction to Schnittke’s narrative. The postmodern anthropologist has discovered Schnittke’s travel records and also starts a journey in search of the Western ‘self’, anthropological dimensions of games and gaming, and the roots of Orientalism in modern times. Echoing the style of Umberto Eco, Roes has written a brilliantly told postmodern adventure novel, which was also submitted as a Habilitation thesis in the subject of Ethnology at the Free University of Berlin. Moreover, in the appendix, Roes not only listed the various games that he observed and described in Yemen, but also he meticulously breaks down the sources used in the historical narrative section, including Ulrich Jasper Seetzen’s Travels through Syria (posth. 1854–1859). My essay addresses the question of how (1.) Roes’s protagonist can be identified with Seetzen and (2.) how orientalism, anthropology, and postmodern self-reflection are related in the novel.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.818
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.275
Teacher spread0.254 · 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 teacher head, not a consensus.

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
Published2025
Admission routes1
Has abstractyes

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