Navigating Equity in Early Learning: Identifying Challenges and Barriers to Early Learning and Childcare for Black Children and Families
Bibliographic record
Abstract
A conducive early learning and childcare (ELCC) environment plays an integral role in the social, emotional, behavioural, and physical development of children. Access to these services is imperative to promote lifelong wellbeing and establish social equity. However, these services are not designed to serve all children. Especially, Black and other racialized children, who face significant disparities both within and outside of these spaces, leading to adverse life outcomes. As receiving adequate education is a social determinant of health, it is imperative that Black and other racialized children can access inclusive ELCC programs and services. Therefore, to optimally support and promote Black children’s health and wellbeing and to address the anti-Black racial gaps in opportunity and achievement, inclusive, comprehensive, and well-coordinated systems of care that reflect the multiple contexts in which Black children are embedded must be provided. To address the objectives of this research, this thesis was conducted in two stages and utilizes mixed methods to investigate the experiences of Black children and their families when accessing ELCC. Stage One was a systematic review of ELCC to determine the common barriers and facilitators that influence access to ELCC. Stage Two was semi-structured interviews (n=25) with Black parents in Kingston and London, Ontario to investigate their attitudes, beliefs, and perspectives on ELCC in their respective cities. Results from this thesis indicate that Black children and their families face unique challenges that decrease their probability of receiving equitable and culturally responsive ELCC. These challenges are typically influenced by multiple intersecting factors that significantly impact their ability to navigate the ELCC system as well as the treatment they receive within the system. Findings from this research can be used to address the barriers faced by Black children and their families. Ultimately, this research can be used to inform policies, programs, and practices that can be established to better serve Black and other racialized children and families and create inclusive and equitable ELCC programs and services.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".