Leblebici, Çiğdem

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https://hdl.handle.net/20.500.14365/7546
Name Variants
Leblebici, C
Leblebici, Cigdem
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Main Affiliation
02.04. Psychology
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Former Staff
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Sustainable Development Goals

NO POVERTY1
NO POVERTY
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ZERO HUNGER2
ZERO HUNGER
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GOOD HEALTH AND WELL-BEING3
GOOD HEALTH AND WELL-BEING
1
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QUALITY EDUCATION4
QUALITY EDUCATION
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GENDER EQUALITY5
GENDER EQUALITY
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CLEAN WATER AND SANITATION6
CLEAN WATER AND SANITATION
0
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AFFORDABLE AND CLEAN ENERGY7
AFFORDABLE AND CLEAN ENERGY
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DECENT WORK AND ECONOMIC GROWTH8
DECENT WORK AND ECONOMIC GROWTH
0
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INDUSTRY, INNOVATION AND INFRASTRUCTURE9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
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REDUCED INEQUALITIES10
REDUCED INEQUALITIES
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SUSTAINABLE CITIES AND COMMUNITIES11
SUSTAINABLE CITIES AND COMMUNITIES
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RESPONSIBLE CONSUMPTION AND PRODUCTION12
RESPONSIBLE CONSUMPTION AND PRODUCTION
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CLIMATE ACTION13
CLIMATE ACTION
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LIFE BELOW WATER14
LIFE BELOW WATER
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LIFE ON LAND15
LIFE ON LAND
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PEACE, JUSTICE AND STRONG INSTITUTIONS16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
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PARTNERSHIPS FOR THE GOALS17
PARTNERSHIPS FOR THE GOALS
0
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Scopus Citation Count

8

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Scopus Citations per Publication

8.00

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Educational and Psychological Measurement1
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    Article
    Citation - Scopus: 8
    Bias in Terms of Culture and a Method for Reducing It: an Eight-Country "explanations of Unemployment Scale" Study
    (SAGE Publications Inc., 2014) Mylonas K.; Furnham A.; Divale W.; Leblebici, Çiğdem; Gondim S.; Moniz A.; Grad H.
    Several sources of bias can plague research data and individual assessment. When cultural groups are considered, across or even within countries, it is essential that the constructs assessed and evaluated are as free as possible from any source of bias and specifically from bias caused due to culturally specific characteristics. Employing the Explanations of Unemployment Scale (revised form) for a sample of 1,894 employed and unemployed adults across eight countries (the United States, the United Kingdom, Turkey, Spain, Romania, Poland, Greece, and Brazil), we applied a method based on individual differences multidimensional scaling and principal component analysis to detect item bias in terms of culture and try to eliminate this bias variance from the overall item variance so as to (a) avoid jeopardizing validity levels and (b) arrive at clearer and more meaningful dimensions after adjusting the raw scores by removing the bias part. The results supported our statistical-psychometric intervention as the structure computed for the unadjusted data was enhanced and clarified when the data were adjusted for bias in terms of culture. Finally, implications for individual assessment procedures are discussed, and a method for evaluating the relative impact of bias in terms of culture on the raw assessment scores is also presented. © The Author(s) 2013.