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Record W4220673006 · doi:10.5430/wjel.v12n2p359

The Compound and Complex Sentence: A Comparative Study of Albanian and English Syntax

2022· article· en· W4220673006 on OpenAlexvenueno aff
Shkëlqim Millaku, Myrvete Dreshaj – Baliu, Xhevahire Millaku

Bibliographic record

VenueWorld Journal of English Language · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics, Language Diversity, and Identity
Canadian institutionsnot available
Fundersnot available
KeywordsSyntaxLinguisticsSentenceComputer scienceGeopoliticsContrast (vision)Artificial intelligenceHistoryNatural language processingPolitical sciencePhilosophyPolitics

Abstract

fetched live from OpenAlex

In the emerging geopolitics of the modern world, English has assumed the undisputed status of the preferred international language of communication. Thus, though cultures across the world are keen on self-preservation, allowing English to make inroads into the everyday lives of the people is a bygone conclusion. Albanian and English belong to the same language family (Indo-European) and hence share many commonalities. At the same time, they also exhibit many features of departure from the shared characteristics, and research into these is greatly significant from the language learners’ vantage. This paper has to analyse the compound and the complex sentence between English and Albanian language. Both these languages have the compound sentences. However, between the two languages, the sentences show certain similarities as well as dissimilarities. We have the contrast structure.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0030.004
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.031
GPT teacher head0.256
Teacher spread0.225 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2022
Admission routes1
Has abstractyes

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