Underrepresentation in Gifted Education Revisited: The Promise of Single-Group Summaries and Meta-Analytic QuantCrit

Results and Discussion

Because numbers are not neutral, it is important to unpack the important population and representation trends. First, as presented in Table 1, the overall representation of Black students in gifted education ranged from 7.40% to 9.90%. However, one nuanced trend related to these percentages is that the representation of Black students in gifted education might be restricted by the size of the overall population of gifted learners. In 2018, there were only 122,256 Black students in gifted education out of 1,661,573, compared with 2014, in which there were 330,774 Black students in gifted education out of 3,329,544. Hence, when more “opportunities” or space exists in gifted programs, more Black students are served, but as space becomes more limited, Black students may experience a greater restriction in terms of access to gifted education compared with their White and Asian peers. Given the centrality of racism, it is important to examine this possible inherent restriction further and consider whether it is a statistical anomaly or an example of “opportunity hoarding.”

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Table 1.

Black Student Representation in Gifted Education Across Three Common Measures of Equity.

Year	n	Representation, %	RDCI, %	Equity Index, %	Inequity Score
2000	240,792	8.23	−51.56	13.59	−0.054
2004	287,828	8.99	−46.74	13.50	−0.045
2006	296,146	9.15	−46.58	13.70	−0.046
2009	316,532	9.86	−44.64	14.25	−0.044
2012	281,135	8.80	−44.65	12.72	−0.039
2014	330,774	9.90	−36.13	12.40	−0.025
2016	276,838	8.50	−44.81	12.32	−0.038
2018	122,256	7.40	−50.99	12.08	−0.047

Note. RDCI = relative difference in composition index.

Data cannot speak for themselves; thus, scholars must improve the national understanding of these trends. The RDCI data indicate that Black students are underrepresented annually by as much as 51.56% and as little as 36.13%. These data correspond to the trends present in the overall representation data. This is understandable because the RDCI is derived from the representation and composition data. Nonetheless, given the extreme and consistent levels of underrepresentation presented in Table 1, it is important to consider why national initiatives and policies that are more equitable are not in place to reduce this inequity in representation.

The EI data tend to be less dependent on the size of the overall gifted population, as trends in data for representation and RDCI indicate, which elucidates that “numbers are not neutral.” Black student representation would need to be increased by between 14.25% and 12.08% to be considered equitable. For instance, in 2018, the overall gifted population was the lowest; this corresponded to the smallest representation of Black students and the largest RDCI observed. However, based on the EI, the necessary increase in Black students to achieve equitable representation was the smallest. At only 12.08%, Black student representation in 2018 was 2.17% less than the largest EI in the data set. This difference in trends results from the 20% equity allowance factor, which helps provide a quantifiable metric of representation that accounts for cultural differences and voluntary exclusion from gifted education programs for students of color (Ford, 2013). Lamb et al. (2019) expanded on Ford’s EI by deriving the IS to indicate the magnitude of inequity present. In Table 1, the IS values range from −0.025 to −0.054, suggesting that Black students are under enrolled in gifted education by 2.5% to 5.4% annually.

A plot of the 95% confidence intervals is presented in Figure 1 to further illustrate these annual trends. The confidence band widths are narrow, indicating that the measures are relatively precise; this is indicative of the large sample sizes present given the representative nature of a national data set. In 2000 and 2014, underrepresentation was extremely high and low, respectively. These values were statistically significantly different from the other observed values (see Finch & Cumming, 2009) and should not be considered when making policy and programming decisions. Including these data would overly complicate interpretation and potentially halt progress toward equity.

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Figure 1.

Single-group summary of 95% confidence interval for Black student inequity scores.

Finally, we provide two upper and lower bounds on the plot. These horizontal lines represent the upper and lower limits of the plausible values for the expected underrepresentation of Black students in gifted education. This range of values is important because it provides a meta-analytic benchmark to help schools gauge their underrepresentation. Specifically, underrepresentation greater than 4.8% is extreme, and underrepresentation less than 3.8% represents a step toward equity.

Conclusion

Quantitative summaries of trends in student representation in gifted education are an important consideration for equity focused meta-analytic thinking, which we define as the utilization of point estimate trends generated from systematic reviews and meta-analyses to identify inequity in independent studies by comparing individual results to mean point estimate trends. In this commentary, we presented a single group summary of Black student representation in gifted education guided by the five tenets of QuantCrit (Gillborn et al., 2018). We hope that this example of equity focused meta-analytic thinking will generate deep reflection and future critical examinations for social justice in gifted education.