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Record W4411516215 · doi:10.54103/2037-3597/29104

LOST IN TRANSLATION: CULTURAL AND PEDAGOGICAL PITFALLS OF WORD-FOR-WORD LANGUAGE TRANSFER IN ITALIAN L2 LEARNING

2025· article· en· W4411516215 on OpenAlexaff
Mohammad Jamali

Bibliographic record

VenueItaliano LinguaDue · 2025
Typearticle
Languageen
FieldComputer Science
TopicLinguistic Studies and Language Acquisition
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLinguisticsLiteral translationIntercultural communicationPsychologySociologyHumanitiesPhilosophySource textPedagogy

Abstract

fetched live from OpenAlex

This paper examines the pitfalls of word-for-word translation in learning Italian as a second language (L2). Drawing on translation studies and language pedagogy, it highlights how literal translations often distort meaning by ignoring cultural, semantic, and pragmatic complexities. Contrary to the belief that direct translation ensures accuracy, this approach frequently leads to awkward or misleading results, e.g., rendering “over easy eggs” as uova super facilmente instead of uova fritte. Italian-specific structures and conventions, such as the formal Lei or idioms like in bocca al lupo, illustrate the deep cultural embedding of language. Three key factors contribute to word-for-word mistranslation: structural differences between Italian and English, false cognates that create semantic confusion, and cultural-pragmatic gaps in idioms and social norms. High-stakes fields like marketing, literature, and international relations underscore the risks of misinterpretation. Advocating a communicative, functional approach, this paper emphasizes the need for cultural literacy, awareness of traditions, idioms, and symbols. It outlines classroom strategies such as contrastive analysis, peer review, and selective technology use. Through examples and case studies, it argues that translation is a process of cultural mediation rather than mechanical substitution. Educators, learners, and professionals must go beyond one-to-one lexical correspondence to foster true intercultural communication. Lost in Translation: Le insidie del trasferimento linguistico parola per parola Questo articolo analizza le insidie della traduzione parola per parola nell’apprendimento dell’italiano come lingua seconda (L2). Basandosi su studi di traduzione e pedagogia linguistica, evidenzia come le traduzioni letterali spesso distorcano il significato, ignorando complessità culturali, semantiche e pragmatiche. Contrariamente alla convinzione che la traduzione diretta garantisca accuratezza, questo approccio porta frequentemente a risultati imprecisi o innaturali, ad esempio, tradurre over easy eggs come uova super facilmente invece di uova fritte. Strutture e convenzioni italiane, come il Lei formale o espressioni idiomatiche come in bocca al lupo, dimostrano il forte radicamento culturale della lingua. Tre fattori principali contribuiscono agli errori di traduzione letterale: le differenze strutturali tra italiano e inglese, i falsi amici che generano confusione semantica e le discrepanze culturali e pragmatiche negli idiomi e nelle norme sociali. Settori di alto profilo come il marketing, la letteratura e le relazioni internazionali mettono in luce i rischi di un’interpretazione errata. Sostenendo un approccio comunicativo e funzionale, questo studio sottolinea l'importanza della competenza culturale, la consapevolezza di tradizioni, espressioni idiomatiche e simboli culturali. Presenta strategie didattiche come l’analisi contrastiva, la revisione tra pari e l’uso selettivo della tecnologia. Attraverso esempi e casi di studio, dimostra che la traduzione è un atto di mediazione culturale, non una semplice sostituzione meccanica. Docenti, studenti e professionisti devono superare la corrispondenza lessicale uno-a-uno per promuovere una comunicazione interculturale autentica.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.446
Threshold uncertainty score0.556

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.056
GPT teacher head0.349
Teacher spread0.293 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2025
Admission routes1
Has abstractyes

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