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Record W2909621699 · doi:10.5539/ijel.v9n1p455

Genre Analysis: Studying Authorial Stance in the Pakistani Research Articles of Business and Management Sciences

2019· article· en· W2909621699 on OpenAlexvenueno aff
Arjamand Bilal, Wasima Shehzad

Bibliographic record

VenueInternational Journal of English Linguistics · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMetadiscourseGenre analysisCompetence (human resources)Academic writingLinguisticsPsychologyOrder (exchange)SociologyMathematics educationSocial psychologyPhilosophy

Abstract

fetched live from OpenAlex

The notion of authorial stance has received much attention internationally in recent years which has increased its complexity in terms of its relationship with genre-pedagogy and genre-awareness. Metadiscourse markers are used by academic writers in order to build and maintain relationship with their readers. This is done by use of appropriate language either to influence them or show a certain degree of agreement or disagreement. The present study investigated the stance features as they appeared in the genre of research article introduction section written by seasoned authors. 50 papers from the field of Business and Management Sciences were studied in order to explore the language features projecting authorial stance or author’s voice used by authors. Hyland’s (2005b) Model of Academic Interaction was used to study the authorial stance. The findings showed that the authors used a considerable degree of stance features in their research articles. The study may provide some useful insights regarding teaching the writing of research article, understanding the concepts of genre-competence and genre-production.

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)0.003
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.853
Threshold uncertainty score0.781

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.080
GPT teacher head0.375
Teacher spread0.295 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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