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Record W2061344602 · doi:10.3138/cmlr.58.2.246

Identifying and Bridging Cross-Cultural Prototypes: Exploring the Role of Collaborative Dialogue in Second Language Lexical Meaning Acquisition

2001· article· en· W2061344602 on OpenAlexvenueaboutno aff
Donald Qi

Bibliographic record

VenueCanadian Modern Language Review/ La Revue canadienne des langues vivantes · 2001
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsnot available
Fundersnot available
KeywordsBridging (networking)LinguisticsSociocultural evolutionMeaning (existential)Sociocultural perspectiveLanguage acquisitionPsychologyNegotiationSituatedSecond-language acquisitionPerspective (graphical)Context (archaeology)Computer scienceSociologyArtificial intelligence

Abstract

fetched live from OpenAlex

Traditional and current lexical pedagogy has not effectively addressed the issue of acquisition of the cultural component of lexical meaning in a cross-cultural context. This paper investigates a pedagogical approach to identifying and bridging the gap between cultural prototypes in second language lexical meaning acquisition. Within the framework of prototype theory and a sociocultural perspective, the author argues, and provides supporting data, that lexical meaning is culturally situated and that teaching and learning of a culturally loaded word may be achieved by teacher and learners' engaging in collaborative inquiries in which meaning is negotiated through interaction with interlocutors' existing knowledge and prior experiences. Four Chinese non-native speakers (NNS) of English and four Canadian native speakers (NS) of English were selected to form four NS-NNS pairs who produced four interactive dialogues. A follow-up test was conducted six weeks after each dialogue. It is demonstrated through analysis of the dialogues and test results that collaborative dialogue may be an effective approach for providing opportunities for active inquiry and negotiation and for promoting acquisition of culturally loaded words in a second language.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.453
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.026
GPT teacher head0.293
Teacher spread0.267 · 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

Citations11
Published2001
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Modern Language Review/ La Revue canadienne des langues vivantesSame topicLanguage, Metaphor, and CognitionFrench-language works237,207