*Names in bold indicate Presenter
The data include standard labor force characteristics such as formal education, age, experience, full-/part-time status and level of responsibility which are essential to developing policies regarding compensation, recruitment and retention. Robust research has demonstrated that worker attitudes and orientations are more predictive of observed caregiving quality and child outcomes than those basic characteristics. The NSECE therefore included a range of tested scales regarding authoritarian vs. progressive beliefs, motivation, stress and depression, asked consistently across all components of the workforce. Additional items having some evidence of association with quality caregiving were also incorporated, including morale, use of curriculum, planning and activities conducted with children. The rich array of information about individual workers, nested in data about their program or home-based setting and their community of location, will provide the basis for several types of analyses including examination of relationships between attributes of workers and compensation and program characteristics, and professional development and program leadership.
From a policy perspective it is important to know the type of program and auspice employing the worker so that appropriate supports or regulations can be devised: a Head Start or public pre-K program, a community-based center, a for-profit or non-profit enterprise, a publicly-available home-based operation that charges fees and serves children to whom the worker does not have a prior relationship vs. an exclusively privately-arranged home setting that serves only children with a prior relationship or does not charge a fee. The NSECE was designed to allow comparison of workers employed in these different types of setting, including almost 4,500 home-based workers, about 1,500 unpaid caregivers and over 5,500 center-based staff.
Findings will be presented overall, and, to the extent possible, by the percentage of low-income children served in a setting and by the poverty density of the geographic community of location. The degree of similarity between these two measures in differentiating the attributes of workers serving low-income children or low-income communities, compared to others, will be an important methodological contribution.