Reconnecting and reclaiming Africentricity: Applying Africentric principles and pedagogy in early learning and child care settings
Bibliographic record
Abstract
An Africentric Early Childhood Education diploma program offered in Nova Scotia (Canada) at the Nova Scotia Community College has been highlighted as a community asset, bringing strength to the early childhood sector. Underpinned by the philosophy of Ubuntu, this pre-service training fosters a supportive learning environment for Black early childhood educators. This research used a Photovoice methodology to explore the application of Africentric principles and pedagogy from participants (n=12) who were graduates of this program and working in early childhood settings during the time of the study. Through a series of workshops, participants identified five key themes: 1) I am the foundation; 2) Connection; 3) Our cultural identity; 4) Self-expression; and 5) Support. Participants referred to themselves as foundational for driving change in early childhood education and curated environments that offered authentic learning experiences of cultural advocacy. At the same time, participants shared feelings of not being supported in their practice as educators, primarily by program administrators, which hindered trust. Participants collectively developed recommendations for the early childhood sector to improve cultural safety and responsiveness. The results from the study are transferable to other educational settings in efforts to challenge systemic racism and ensure safe working environments for educators.
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 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 | 0.014 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.014 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.002 |
| 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".