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Record W1948661721

A COMPARATIVE STUDY OF THE TEXTUAL FEATURES OF IRANIAN AND ENGLISH RECOMMENDATION LETTERS

2014· article· en· W1948661721 on OpenAlexaboutno aff
Elaheh Tajik Qanbari, Majid Nemati, Iman Tohidian

Bibliographic record

VenueJournal of Teaching English for Specific and Academic Purposes · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDigressionBridge (graph theory)LinguisticsTest (biology)PsychologyPhilosophyBotany
DOInot available

Abstract

fetched live from OpenAlex

Analysis of different academic writings to obtain cross-cultural differences, Recommendation Letters is still considered as a Cinderella among Iranian scholars. Adopting the Clyne's (1991) framework to analyze English recommendation letters written by Iranian, American, Canadian, and British university professors, to see if there is any significant difference between these two types in terms of digression, textual symmetry, integration, advance organizers, enumerative sentences, bridge sentences, and topic sentences, forty-seven RLs were collected in total, 27 of which were written by Iranian university professors and 20 by those native speakers of English. Having analyzed the letters according to those features, a Chi 2 test was conducted to demonstrate the results statistically. It was found that there are significant differences between these two groups of letters regarding textual symmetry and topic sentences, while there were no significant differences regarding digression, data integration, advance organizers, enumerative sentences, and bridge sentences.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.176
Threshold uncertainty score0.255

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.044
GPT teacher head0.346
Teacher spread0.303 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations2
Published2014
Admission routes1
Has abstractyes

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