MétaCan
Menu
Back to cohort
Record W2152298332

An alternative approach to speech act research in the study abroad context

2013· dissertation· en· W2152298332 on OpenAlexfundaboutno aff
Victoria Surtees

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2013
Typedissertation
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsnot available
FundersConcordia University
KeywordsContext (archaeology)Study abroadSpeech actPsychologyOnline communityMedical educationPedagogyLinguisticsComputer scienceMedicineWorld Wide WebGeography
DOInot available

Abstract

fetched live from OpenAlex

This research aims to contribute to a description of the breadth of opportunities for L2 contact and pragmatic development offered by the Canadian study abroad (SA) context by taking an alternative approach to speech act research. This study reports on the frequency and range of L2 speech acts and events as described by SA students in interaction logs completed with their mobile phones. Nine undergraduate SA students completed structured electronic surveys (n = 801) regarding their English oral interactions over ten-day period. The participants, from various disciplines, proficiencies and L1 backgrounds, were attending an English-speaking university in Montreal as part of a one- or two-semester academic exchange. Participants completed the two-three minute online survey each time they interacted orally in English, describing the content of each interaction, the interlocutors involved, and the location in addition to rating its difficulty. Results showed frequent exchanges on cultural issues with other international students and a low percentage of native interaction, suggesting that SA students have the opportunity to perform a range of speech acts and events but do so within their own peer community. Implications for the describing pragmatic development in SA speech act research are discussed.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.349
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0050.000
Research integrity0.0000.003
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 head0.114
GPT teacher head0.380
Teacher spread0.266 · 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 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

Citations1
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueSpectrum Research Repository (Concordia University)Same topicLanguage, Discourse, Communication StrategiesFrench-language works237,207