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Record W3176869835 · doi:10.5539/ijel.v11n4p40

Preposition Pied Piping and Stranding in Academic and Popular Nigerian English Writing

2021· article· en· W3176869835 on OpenAlexvenueno aff
Roseline Abonego Adejare

Bibliographic record

VenueInternational Journal of English Linguistics · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPipingNatural (archaeology)LinguisticsFormalityHistoryMathematicsLiteratureArtEngineeringPhilosophyArchaeologyMechanical engineering

Abstract

fetched live from OpenAlex

This paper examined preposition pied piping and stranding in academic and popular Nigerian English writing with a view to determining their pattern of occurrence. Preposition placement has not been studied in Nigerian English and in specific genres. The 160 246-word relevant component of ICE-Nigeria was the sub-corpus used, and the Systemic Theory guided the study. Analysed using a multi-layered qualitative approach, the data comprised 112 cases of pied piping, 64 of stranding and 4 of doubling. Pied piping was dominant over stranding in Academic Writing (78 percent v 22 percent), and stranding was 1.7 times more frequent in Popular Writing than in Academic Writing. Though evenly distributed in Popular Writing (44 each), pied piping was about twice as frequent as stranding in Popular Natural Sciences while stranding was virtually non-existent in Academic Natural Sciences. Whereas to-infinitive and passive clauses were stranding favourite sites (21 and 15 respectively), only in wh-relative clauses did pied piping operate and in which was the prominent sequence. In Academic Writing prepositions were pied-piped and stranded at an average of 3.83 and 1.82 per form respectively, but the rates were 3.31 and 3.1 in Popular Writing. Whereas in was the most pied-piped preposition and was 5.2 times more likely to be pied-piped than stranded, up was the most stranded form and its stranding relative to pied piping was infinitely more. Subtle differences in the genres’ degree of formality explain the disparities in the distribution of pied piping and stranding in the sub-corpus analysed.

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)0.000
metaresearch head score (Gemma)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.022
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 head0.023
GPT teacher head0.301
Teacher spread0.277 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of English LinguisticsSame topicDiscourse Analysis in Language StudiesFrench-language works237,207