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Record W2620015375 · doi:10.1080/00223891.2017.1324458

Validation of the Empathy Quotient in Mainland China

2017· article· en· W2620015375 on OpenAlexaboutno aff
Qing Zhao, David L. Neumann, Xiaoyan Cao, Simon Baron‐Cohen, Xiang Sun, Yuan Cao, Chao Yan, Yuna Wang, Lin Shao, David Shum

Bibliographic record

VenueJournal of Personality Assessment · 2017
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsnot available
FundersGriffith UniversityNational Institute for Health and Care Research
KeywordsPsychologyEmpathyInterpersonal Reactivity IndexMainland ChinaAutismConfirmatory factor analysisClinical psychologyAlexithymiaInterpersonal communicationPsychometricsDevelopmental psychologyStructural equation modelingChinaSocial psychologyStatisticsPerspective-taking

Abstract

fetched live from OpenAlex

This research aimed to validate a simplified Chinese version of the Empathy Quotient (EQ; 60 items) for use with Mainland Chinese people. The original English version of the EQ was translated into simplified Chinese. Through an online survey, 588 Mainland Chinese participants completed the EQ and 3 other questionnaires: the Interpersonal Reactivity Index (IRI), the Autism-Spectrum Quotient (AQ), and the 20-item Toronto Alexithymia Scale (TAS-20). Thirty-five participants completed retesting of the EQ 3 to 4 weeks later. Sex differences on the EQ scores and psychometric properties of the EQ items were examined. Confirmatory factor analysis suggested that an EQ 15-item structural model fitted the data quite well. Self-report empathy, as assessed by the current simplified Chinese version of the EQ, appeared to relate to participants' autistic and alexithymic traits but not sex.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.224

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.053
GPT teacher head0.378
Teacher spread0.325 · 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 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

Citations44
Published2017
Admission routes1
Has abstractyes

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