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Record W3035555667 · doi:10.1075/cilt.350.13bub

The rise of the analytic Perfect aspect in the West Iranian languages

2020· book-chapter· en· W3035555667 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

VenueAmsterdam studies in the theory and history of linguistic science. Series 4, Current issues in linguistic theory · 2020
Typebook-chapter
Languageen
FieldArts and Humanities
TopicLinguistics and language evolution
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsGrammaticalizationPersianSection (typography)LinguisticsSlavic languagesPresent perfectHistoryMathematicsComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

Abstract This paper focuses on the long-term grammaticalization of tense/aspect systems in the West Iranian languages, beginning with Old Iranian ( Section 1 ). In Middle Persian ( Section 2 ) the Aorist and the reduplicative Perfect of Old Persian were replaced by a new system of analytic constructions. The fundamental mechanism in the rise of the innovative Preterit (perfective) and Perfect categories was the process of grammaticalization, reducing the auxiliary ‘be’ into suffixes of the innovative Preterit. In Early New Persian ( Section 3 ) an unambiguous Perfect was recreated by attaching personal suffixes to the Perfect stem. In the second part of the paper ( Section 4 ) we turn to the elaboration of the evidential (‘non-witnessed’) subsystem in New Persian through grammaticalization and possible Turkic influence. A typological parallel in the southernmost Slavic languages ( Section 5 ) is provided.

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)0.011
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.956
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.019
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
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 head0.042
GPT teacher head0.305
Teacher spread0.263 · 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