Other demographic biases such as generation and gender are also rich areas for research exploration. MRG’s research shows the different approaches to leadership based on age and based on gender. To explore the dynamics of gender bias MRG recently conducted a study to examine the rating patterns in the LEA360 based both on the gender of the rater and the gender of the individual being rated. The results of that study show very specific patterns of gender bias based on both the gender of the rater and the gender of the person being rated. Studies like these and others conducted by MRG are readily shared with practitioners certified in our assessments to help them navigate through, and help their clients navigate through, the complexities of human bias in the workplace.
Shreya Sarkar-Barney ∙ These biases are less of an issue when one relies on meta-analyses and not findings from individual studies.
Most leadership assessment tools are descriptive, which means they help describe a facet of leadership but may not provide a forward-looking view of what a leader is likely to do. The later requires building predictive tools. Such endeavors take time to build, as they require testing the validity of the instrument across samples and across time. The bias for leaning on science allows us to draw upon the 1000s of studies that are continuously evolving our understanding and ability to more accurately measure leadership. It ensures that the tools we build are backed by a rock-solid foundation in prediction and explanation. Further, instruments should undergo rigorous psychometric evaluations to ensure they meet four critical gold standards.
(a) Reliability – the instrument consistently measures the attributes of interest for the same individual and across individuals, (b) Differentiating – the instrument measures the full spectrum of the attribute on a yardstick as opposed to only middle range scores, (c) Validity – the instrument accurately measure the attributes of interest, and (d) Predictive – the instrument scores provide a forward-looking view of the phenomenon of interest with a high level of accuracy.
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