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Record W1909577413 · doi:10.18806/tesl.v30i7.1151

"Please consider my request for an interview": A Cross-cultural Genre Analysis of Cover Letters Written by Canadian and Taiwanese College Students

2014· article· en· W1909577413 on OpenAlexvenueaboutno aff
Hsiao-I Hou

Bibliographic record

VenueTESL Canada Journal · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
FundersNational Science Council
KeywordsRhetorical questionLinguisticsSentencePsychologyVariety (cybernetics)Cover (algebra)Cross-culturalSociologyComputer science

Abstract

fetched live from OpenAlex

In this study, similarities and differences among generic structures in 80 cover letters written by Taiwanese and Canadian college students were investigated, adopting Upton and Connor’s (2001) framework. The results demonstrated that Canadian students tend to write longer letters, use a greater variety of word types and sentence structures, and choose more professional words than do Tai- wanese students. From the moves-based analysis results, the study revealed that to achieve the main communicative purpose of a cover letter, which is to be con- tacted for an interview, the Canadians employed lengthy sentences and various strategies to demonstrate their qualifications. By contrast, Taiwanese students employed different communicative elements, including direct strategies to ex- press their desire for an interview and uses of formulaic expressions that were not observed in the Canadian corpus. The research findings suggest that the move- structural and rhetorical differences are due to writers’ differences in cultural backgrounds and their rhetorical and lexical knowledge of the particular genre. The results of this study provide implications for teaching English for specific purposes to nonnative speakers.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.025
GPT teacher head0.305
Teacher spread0.280 · 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.

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

Citations9
Published2014
Admission routes2
Has abstractyes

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