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Record W3005140370 · doi:10.5539/ijel.v10n2p159

Lexical Enrichment in English and Kurdish: A Comparative Study

2020· article· en· W3005140370 on OpenAlex
Khalid A. Abdullah, Soran Abdulrahman Hemed

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of English Linguistics · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLinguisticsSection (typography)Computer scienceLexical itemProcess (computing)Natural language processingPhilosophyProgramming language

Abstract

fetched live from OpenAlex

The present study is a comparative study of lexical enrichment between English and Kurdish. It aims to compare the methods and the processes by which new words are formed and/ or new lexical items come to the languages. It explains how both languages can be enriched and which method or process is more common and productive than others in the two languages. The study consists of two sections. The first section is about the ways and the methods of lexical enrichment in English. The second section is about lexical enrichment in Kurdish in which similarities and differences are explained between the two languages. At the end of the study there are some important conclusions taken from the research, a list of Kurdish phonemic symbols and a list of English and Kurdish references.

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.

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)0.023
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.892
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.023
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 head0.066
GPT teacher head0.306
Teacher spread0.240 · 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