Early Childhood Teacher Education in Namibia and Canada
Bibliographic record
Abstract
Abstract This comparative and qualitative study-in-progress focuses on two early childhood teacher education (ECTE) programs in contexts where the participants are undergoing rapid social and personal change: a program in Namibia and a training program for immigrant childcare educators in Canada. The objective is to provide in-depth understanding of the ways in which differing ideas about ECTE are reflected in practice. It is important to ensure that ECTE programs prepare teachers to dovetail children’s preparation for school with meaningful connections to the culture and language of the home community, since more and more children spend their preschool years in early childhood (EC) centers that are becoming increasingly westernized in character. Without such connections, children in settings undergoing rapid change will continue to drop out of school before literacy and other skills are firmly established. The data will stem from analysis of early childhood care and education and ECTE curricula; policy and other documents; focused observations in ECTE classrooms and teaching practica; and interviews with teacher educators, education officers, teachers, parents, and community leaders. The results are expected to illuminate issues and strategies which are most likely to be effective for ECTE programs, with implications for teacher education in a range of settings in both the majority and minority worlds.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.017 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".