Exploring an Historical Transition in Early Childhood Education in Ontario
Bibliographic record
Abstract
This predominantly qualitative study looks at the current changes in early childhood education in Ontario, Canada from an early childhood education leadership perspective. The analysis and recommendations resulting from my dissertation adds to the growing body of work examining the rapidly changing landscape of the early years. My dissertation utilizes a constructivist lens to reconstruct perspectives surrounding matters of importance in a field that is on the cusp of obtaining true professional recognition.\nWith the advent of a self-regulating body (College of Early Childhood Educators) and a shift in management from the Ministry of Children and Youth Services to the Ministry of Education, the study highlights some of the changes occurring in the early years sector, both institutionally and professionally. The ensuing data was collected through 35 interviews of early years champions and 167 surveys from various early years teacher-educators and practitioners, revealing strong topics of discussion that add to the cacophony of voices heralding demands that the early childhood educator be perceived and treated as an equal participant in the education system.\nOf the 8 themes that emerged from the data analyzed, 3 were the focus of this study. The first theme focused on leadership, including characteristics of leaders and themes of emerging leadership; the second on professionalization of the early years sector (Feeney, 2012): for example, consistency in terminology, pay equity, universality, and issues regarding the current infrastructure; and the third theme investigated was intellectualization as part of the professional process: for instance, current curriculum focus, higher-learning demands, ongoing learning, the value of lab schools, faculty responsibilities, and specialization as a means of differentiated staffing (Zigler, Gilliam, & Barnett, 2011). This study also includes miniature profiles of the early years leaders interviewed, and a synopsis of their personal journeys to leadership.\nIn the concluding chapter, the recommendations presented suggest various ways that current and emerging early years leaders can make positive impact within this transforming sector. Empowerment of self, recognition of professional status, and a view to the long-term visioning of education provides the impetus for change.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.032 | 0.017 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".