Exploring the Emotional Intelligence Construct: A Cross-Cultural Investigation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Test transportability is a prevalent issue in psychological measurement. Oakland (2004) report that foreign developed tests are used, in most countries, more frequently than nationally developed tests. The main aim of this research was to differentiate cultural bias from true construct variance in a self-report measure of Emotional Intelligence (EI) in the workplace (the Swinburne University Emotional Intelligence Test, SUEIT; Palmer & Stough, 2001). Such investigations are necessary as tests of EI are increasingly being used extensively around the world. For example, the Twenty-item Toronto Alexithymia Scale-III (TAS-20) (Parker, Taylor & Bagby, 2003) has been translated into 18 languages. The Bar-On Emotional Quotient Inventory (EQ-i, Bar-On, 1997) has 22 language translations and normative data is available in more than 15 countries (Bar-On, 2000). This investigation focused on the generalisability and transportability of the SUEIT, a prominent self-report monocentered (i.e. instrument from a single, Western cultural background; Van de Vijver & Leung, 2001) EI measure to two Western (USA, New Zealand) and four non-Western countries (Italy, South Africa White and Non-White, Sri Lanka). It could be argued that the Western cultural origin of the test (i.e. Australia) contains descriptions of EI as defined within Australian culture. Cultural dimension differences (Hofstede, 1980, 2001) could introduce cultural bias into Western EI measures on various levels, when applied in non-Western environments. On a broad conceptual level the central research question this study aimed to investigate can be formulated as follows: to what extent do Hofstede (1980, 2001) cultural dimensions systematically influence the cross-cultural transportability of a self-report EI measure? Measurement invariance (configural and metric invariance; VandenBerg & Lance, 2000), method bias (national differences in response styles, i.e. extreme response styles and acquiescence; Van Herk, Poortinga, & Verhallen, 2004; as well as negatively keyed method factors) and the differential item functioning (uniform and non-uniform DIF were investigated with a series of Mean and Covariance Structures Analyses models run in LISREL 8.8; Chan, 2000) of the SUEIT over the various samples, were investigated. It was argued that the amount of cultural bias would increase as the Cultural Distance (CD, the extent to which cultures are similar or different; Shenkar, 2001) (Kogut & Singh, 1988) between a given cultural group (e.g. Sri Lanka) and Australia increase. That is, the more a particular culture is dissimilar to Australian culture (origin of the SUEIT) the more pronounced the influence of culture will be on the transportability of the instrument. In addition, latent mean differences (derived from partially constrained SEM models) in the different SUEIT EI subscales were also investigated. Overall the results of the construct, method and item bias investigations suggested that the transportability of the instrument is not severely affected when used in other Western cultures. Almost no significant latent mean differences on the various EI facets were evident between Western cultural groups (i.e. New Zealand and USA compared to Australia). Evidence of cultural bias, when the instrument was applied to respondents from non-Western cultures, was found. In addition, notable significant latent mean differences between Australia and the non-Western cultural groups, on various EI facets, emerged. The results suggest that it may be necessary to adapt the SUEIT for future cross-cultural use. The practical implications of the results within the workplace, as well as limitations of the study and recommendations for future research were discussed.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it