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Record W7010672334

IRANIAN UNIVERSITY STUDENTS’ PERCEPTIONS OF THEIR SOCIAL INTERACTIONS IN CANADA

2008· article· en· W7010672334 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2008
Typearticle
Languageen
FieldComputer Science
TopicSolar Radiation and Photovoltaics
Canadian institutionsnot available
Fundersnot available
KeywordsPerceptionGrounded theoryQualitative researchPronunciationGrammarSemi-structured interviewSocial relationImmigration
DOInot available

Abstract

fetched live from OpenAlex

This study investigated the dynamics of adult Iranians’ social interactions in Canada. The purpose was to identify social and cultural factors that improve or block speaking opportunities for adult Iranian immigrants. Eight Iranians, five men and three women, who had spent their adulthood in Iran, accepted invitations to participate in this study. They were interviewed for their processes of English language learning and their social interactions in Canada. The interviews were conceptualized for themes using the principles of grounded theory methodology. The analysis demonstrated that adult Iranians faced various challenges in their social interactions in Canada. Over-monitoring of grammar and pronunciation impediments turned out to be their main linguistic challenges. Opportunities for speaking with Canadians and cultural factors such as gender issues, religious background and personal background were the other factors emerging out of data analysis as influencing their social interactions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.123

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0110.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.089
GPT teacher head0.300
Teacher spread0.212 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2008
Admission routes1
Has abstractyes

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