Introduction – Racial inequalities in public child welfare systems have been well documented; children of color are disproportionately represented and often experience poorer outcomes than their white counterparts. However, workers of color are often proportionately *more* represented in public child welfare than in general populations (Dolan et al., 2011). And while there is a wealth of research on client disproportionality, far less attention has been paid to the experiences of workers of color.
Existing research has explored how a worker’s intent to leave the agency is related to perceptions of workplace inclusion. Researchers have found that public child welfare workers of color report feeling public child welfare is “white-normed” (Gosine & Pon, 2011), that they are treated less fairly, and they are less likely to be supervisors (Lawrence et al., 2020). These are thought to play a role in higher rates of intent to leave (Griffiths et al., 2017) as compared to their white counterparts.
Modern public child welfare is more racially diverse than ever (Dolan et al., 2011). However, simply “diversifying” a public child welfare workforce is not a panacea for a culture often described as a “handmaiden of the status quo” (Abramovitz, 1998; Davis & Gentlewarrior, 2015). Hiring workers of color without shifting culture can leave those workers vulnerable to racism manifested in micro-aggressions and discrimination in promotion/advancement.
Gap – Only one study has focused on the relationship between organizational climate of inclusion and intent to leave in public child welfare workers of color (Hwang & Hopkins, 2015). More is needed to gain a fuller picture of the nature of these factors’ relationships.
Theoretical framework – Inclusion is modeled by Shore and colleagues (2011, 2018) as valuing uniqueness and promoting belongingness. Uniqueness involves individuals maintaining distinctive and differentiated senses of self; belongingness speaks to having strong, stable interpersonal relationships and feeling like an “insider.”
Data Analysis – Ordinal logistic regression was used to analyze a cross-sectional statewide sample (n=3,481) of public child welfare workers in Texas. Descriptive statistics and multiple imputation were run (and checked), and confirmatory factor analysis was used to fit two measurement models (uniqueness and belongingness). Resulting latent variables were used as predictors of respondents’ intent to leave.
Findings – Workers who identified as Black, African American, or multi-racial were more likely to intend to leave than their white counterparts, and this was significantly modified by perceptions of inclusion. The same was not found for workers who identified as Hispanic or Asian.
Implications – Public child welfare agencies have prioritized hiring a more racially diverse workforce. Recruiting more workers of color without working toward a more inclusive organizational culture can lead to higher turnover in precisely these workers agencies seek to retain. Building a more inclusive organizational culture has the potential to move closer to racial equity in public child welfare.