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Record W2801351417 · doi:10.5539/ijel.v8n4p253

The Equivalence and Nonequivalence of Proverbs Across Cultures (Indonesian and English)

2018· article· en· W2801351417 on OpenAlexvenueno aff
Syahron Lubis

Bibliographic record

VenueInternational Journal of English Linguistics · 2018
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsnot available
FundersUniversitas Negeri MedanUniversitas Sumatera Utara
KeywordsIndonesianMeaning (existential)LinguisticsEquivalence (formal languages)SentenceMetaphorLexical itemLiteral and figurative languagePsychologyPhilosophy

Abstract

fetched live from OpenAlex

The aim of the present study is to examine whether or not proverbs, culturally-related medium of communication, are equivalent across cultures. The proverbs compared are derived from Indonesian and English cultures, as two distinct cultures. Fifteen Indonesian proverbs and fifteen English proverbs have been compared to find out whether or not they are equivalent in terms of meaning, linguistic structure and culture. The proverbs are collected from a list of well-known Indonesian and English proverbs. Since almost the thirty proverbs are expressed in metaphorical meaning and since Indonesian is still foreign to many international readers the literal meaning of lexical items found in the proverbs have been glossed in brackets followed by the explanation of the metaphorical meaning of the thirty proverbs. Ten Indonesian proverbs are found to be equivalent in terms of meaning to ten English proverbs. In terms of linguistic structure they are almost equivalent that is they are expressed mostly in the form of sentence. But they are different in the use of lexical items that constitute the proverbs. Five Indonesian proverbs are found to be nonequivalent to five of English in terms of meaning and the lexical items used to build the metaphor. Thus it is found out that fifteen Indonesian proverbs are equivalent to fifteen English proverbs and five Indonesian proverbs are found to be nonequivalent to five English proverbs.

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)0.027
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 score0.720
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.027
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 head0.017
GPT teacher head0.340
Teacher spread0.323 · 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 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

Citations2
Published2018
Admission routes1
Has abstractyes

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Same venueInternational Journal of English LinguisticsSame topicLanguage, Metaphor, and CognitionFrench-language works237,207