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Record W2338387800 · doi:10.1177/0008429816637637

Part Lion, Part Wolf

2016· article· en· W2338387800 on OpenAlexvenueno aff
Mathieu E. Courville

Bibliographic record

VenueStudies in Religion/Sciences Religieuses · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Studies and History
Canadian institutionsnot available
Fundersnot available
KeywordsNovellaOrientalismParallelsPoliticsKey (lock)LiteraturePhilosophyHistoryAestheticsArtPolitical scienceLaw

Abstract

fetched live from OpenAlex

In this essay, I begin by examining arguments concerning “Orientalism” from the work of the late Edward W. Said. I then highlight the way that Kurban Said’s novella Ali and Nino is indebted to this tradition, the author relying upon it in order to create a complex world within a few pages. On the one hand, this novella is a wonderful work of art with which to work out some of Edward Said’s key ideas, and on the other hand, appreciating Edward Said’s key ideas is also crucial for a better appreciation of this novella’s complexity. The second part of the paper focuses on the novella itself, so as to think of Ali and Nino with Edward Said’s critique of Orientalism in the foreground of one’s mind. In conclusion, I not only highlight why this also sheds light on art and literature, religion and politics, history and current affairs, in such a geopolitically important area as the Caucasus as well as elsewhere the world over; I also point out parallels between the Orientalist stereotypes examined in this essay and key ideas from ascetic religious traditions.

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)0.003
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.051
Threshold uncertainty score0.170

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0060.004
Open science0.0000.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0510.014

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 head0.088
GPT teacher head0.379
Teacher spread0.291 · 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
Published2016
Admission routes1
Has abstractyes

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