Exploring early childhood educators’ notions about professionalism in Prince Edward Island
Bibliographic record
Abstract
Despite policy changes in a growing number of countries to increase the quality of early years education through the introduction of national curricular frameworks, conceptualizations of early childhood professionals remain distinctly variegated. Early learning curriculum frameworks have become embedded into the 21st-century early learning movement, creating a shift in professional deliverables and system expectations. This study explores how early childhood educators (ECEs) in Prince Edward Island (PEI) understand the concept of professionalism in their everyday practice. The researchers used qualitative methodology and a variety of methods, including workshops, interviews, and field notes, to gain insight into how ECEs understand professionalism. The data was analyzed through thematic analysis and understood through the lens of sociocultural theories of learning that embrace communities of practice as a positive way to promote professional learning. Primary findings explore (1) how ECEs understand professionalism in PEI, (2) positive and negative impacts on their understanding of professionalism in their daily practice, and (3) professional development opportunities that impact professionalism in the early childhood field.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".