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Defining relationships: Comparing Canadians, Chinese and Indians

2006· article· en· W2156563213 on OpenAlexaffabout
Han Z. Li, Gira Bhatt, Zhi Zhang, Jasrit S. Pahal, Yanping Cui

Bibliographic record

VenueAsian Journal Of Social Psychology · 2006
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsKwantlen Polytechnic UniversityUniversity of Northern British Columbia
Fundersnot available
KeywordsClosenessSocial psychologyPsychologyChinaSample (material)Asian IndianDemographyDevelopmental psychologySociologyGeographyMathematics

Abstract

fetched live from OpenAlex

To examine whether cultural differences exist in defining family, friend, relative, colleague and neighbour, non‐student samples were drawn from Canada, China and India. The data generated several unexpected findings. (i) The means of the relationship definitions between the Chinese and Canadians were not significantly different. The means between the Chinese and Indians were significantly different. The means between the Canadians and Indians were significantly different. (ii) Females defined their relationships more interdependently than males in the Indian and Canadian samples but not in the Chinese sample. (iii) Definitions were target specific and the order of closeness differed from group to group. (iv) In the Indian and Chinese samples, participants’ age was negatively correlated with closeness in defining friends, indicating that a person’s perceived closeness with friends changes over the life span. Results of past research using student samples need to be interpreted with caution.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score0.317

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0040.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.067
GPT teacher head0.385
Teacher spread0.318 · 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

Citations4
Published2006
Admission routes2
Has abstractyes

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