MétaCan
Menu
Back to cohort
Record W1563889601

Manifestation of Social Trust among Migrants: The Case of Iranian Residents in Toronto, Canada

2012· article· en· W1563889601 on OpenAlexaboutno aff
Mahmood Ketabi, Vahid Ghasemi, Mojtaba Mahdavi

Bibliographic record

VenueInternational journal of criminology and sociological theory · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Capital and Networks
Canadian institutionsnot available
Fundersnot available
KeywordsSocial trustScale (ratio)Sample (material)PsychologySocial psychologySignificant differenceGeneral Social SurveyDemographySociologyGeographySocial scienceSocial capitalMedicine
DOInot available

Abstract

fetched live from OpenAlex

This paper is excerpted from a research project titled “A Sociological Analysis of Socio-economic Situation of Iranian Migrants in Canada (Case Study: Toronto). This survey research has been carried out in 2005. Its main goal is to answer the following questions: What is the trust level among Iranian migrants residing in Toronto? What is the difference between the in-group social trust level (trust among Iranians) and the out-group trust level (confidence toward Canadians living in Toronto)? In an attempt to answer these questions a sample of 182 Iranians were interviewed on the basis of a standardized questionnaire. The findings reveal that the in-group social trust level – as measured against the defined scale – is slightly below the average, whereby the difference from the middle point of the scale is statistically significant. Moreover, it demonstrates that the mean figure for out-group social trust is significantly higher than the average defined on the scale. The results also suggest that the most important cause for lower in-group trust should be sought for in the pre- migration period. Researches carried out on social confidence indicate that weakness of social trust in home country is often transferred to other countries – after migration – and is intensified due to problems of the migrant community and increase of social risk.

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)0.002
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.717
Threshold uncertainty score0.841

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.046
GPT teacher head0.343
Teacher spread0.297 · 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 designTheoretical or conceptual
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
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueInternational journal of criminology and sociological theorySame topicSocial Capital and NetworksFrench-language works237,207