Contributing to an ecology of knowledges for understanding the education neglect of children in care: perspectives from school social workers and educators
Bibliographic record
Abstract
Children in care (CIC) in Manitoba face persistent educational disparities, with low high school graduation rates serving as a major barrier to post-secondary access and future well-being. Despite long-standing concerns, the educational neglect (EN) of CIC remains critically underexamined and largely unreported, perpetuating their invisibility within policy and practice. This study investigates how the perceptions of school social workers, teachers, and Indigenous education team members contribute to an ecology of knowledges that deepens the understanding of the EN of CIC. Insights from Indigenous knowledges and developmental cognitive neuroscience provide context for understanding healthy child development and the effects of adverse childhood experiences. Given that most CIC in Manitoba are Indigenous, this demographic reality was carefully considered and reflected across all aspects of the study and its reporting. Employing a Critical Constructivist Grounded Theory methodology, this qualitative inquiry engaged 17 participants across Manitoba through semi-structured interviews. Data were analyzed using Charmaz’s grounded theory methods, guided by the Critical Theory of Coloniality (CTC) for reflexive and critical engagement with colonial, neoliberal, and systemic power dynamics. Three major themes emerged: (1) colonization, neoliberalism, and power—illuminating how structural inequities perpetuate the marginalization of CIC; (2) educational repair—emphasizing the need for coordinated and individualized supports that emphasize attachment and belonging; and (3) Healing education—centering trauma-informed, relational, and culturally responsive approaches to learning and care that empower CIC. From these findings, the Transformative Care-Education Theory was developed, offering a framework that integrates a CTC perspective as a starting point to address the EN of CIC. The study underscores the urgent need for collaborative policy mandates, culturally grounded training, and cross-sector partnerships to confront educational inequities faced by CIC. This research study contributes to transformative approaches in the practice, policy, and professional education of social workers and educators. Its findings also hold relevance for related disciplines engaged in supporting children and families who are involved with child welfare.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.026 | 0.036 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".