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Record W2015127755 · doi:10.1080/00210860701786603

Simin Behbahani's Poetic Conversations

2008· article· en· W2015127755 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

VenueIranian Studies · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Studies and History
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPoetryConversationSensibilityLiteratureDramaFace (sociological concept)Character (mathematics)FemininityStyle (visual arts)AestheticsSociologyArtPhilosophyLinguisticsCommunicationGender studies

Abstract

fetched live from OpenAlex

From the beginning of her career, Simin Behbahani stresses her intention to reflect contemporary concerns in her poetry. She has continued to use the traditional form of ghazal and to affirm the ghazal 's capacity to reflect the contemporary environment. Behbahani tells us how she changed the structure of the ghazal to suit her poetic needs. This paper focuses on the poetic conversation as a feature of Behbahani's poetic style which leads her poetry firmly into present time. Early female poets in Iran made use of poetic conversation to bring attention to a changing social system and, especially, issues of concern to women. Behbahani refines and perfects the technique of poetic conversation. Her poetic conversations range from a single-voiced complaint to complex commentary involving more than one perspective. In particular, a character identified only as “you” at times represents society or a companion, and may even bring the poet face-to-face with herself. This character widens the scope of the poetic drama. Behbahani's poetic conversations convey a femininity that is complex and a sensibility that is modern.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.711
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
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 head0.115
GPT teacher head0.342
Teacher spread0.227 · 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