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Record W4292342613 · doi:10.1016/j.heliyon.2022.e10241

The very first sentence in research article introductions: A rhetoric comparative approach

2022· article· en· W4292342613 on OpenAlexaboutno aff
Mohammad Saud Alanazi, Muteb Alqarni

Bibliographic record

VenueHeliyon · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSentenceLinguisticsRhetoricQuarter (Canadian coin)Space (punctuation)Contrast (vision)SociologyPsychologyHistoryComputer scienceArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

The current study explores the rhetoric and stylistic properties of the very first sentence that scholars generate in their research article introductions. The study draws upon a corpus of 502 sentences written in the fields of linguistics and translation, half of which are collected from national low-impact journals affiliated with Gulf universities in the Middle East while the other half are elicited from international high-impact journals. The study shows that half of the authors in high-impact journals as opposed to a quarter of the authors in low-impact journals provide citations to their very first sentence. These preferences are accounted for by the distinction drawn by Swales (1990) between centrality claims and topic generalizations under Move 1. Contra the predictions made by Create A Research Space Model proposed by Swales (1990, 2004), the results show that the authors of high-impact journals are more liberal in starting their introduction with a sentence of Move 2 or 3 type. In contrast, the authors of low-impact journals prefer to begin with a sentence of Move 1 type that is shorter in word count, more metaphorical, less academic as well as full of typos and grammatical errors.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.529
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.154
GPT teacher head0.361
Teacher spread0.207 · 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 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
Published2022
Admission routes1
Has abstractyes

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