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Teaching Persian to Speakers of Other Languages

2018· book· en· W2891566500 on OpenAlex
Pouneh Shabani-Jadidi, Anousha Sedighi

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

VenueOxford University Press eBooks · 2018
Typebook
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsPersianLinguisticsVariety (cybernetics)PsychologyHistoryComputer scienceArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

Teaching and learning Persian as an additional language is facing unprecedented demand inside and outside the Persian-speaking counties. This chapter discusses teaching Persian to speakers of other languages from a variety of perspectives. It provides a short account on the history of teaching Persian in non-Persian-speaking countries and discusses the current status of teaching Persian to speakers of other languages both in the east and the west. The chapter also discusses second-language acquisition studies on Persian as well as the recent trends on pedagogy and assessment. It also investigates the development of the Persian instructional material and discusses the available Persian textbooks. Lastly, the current issues and challenges of teaching Persian to speakers of other languages is discussed and explored.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.701
Threshold uncertainty score0.590

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 studies0.0000.000
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 head0.027
GPT teacher head0.291
Teacher spread0.264 · 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