Professionalization in early childhood education: how do educators craft their work?
Bibliographic record
Abstract
Job crafting offers an exciting way to understand how people engineer their jobs to create more meaningful work. Work is meaningful if workers perceive their work as significant and serving an important purpose. To examine how four early childhood educators individually and collaboratively craft their work, the study reported here examines data from a case study in a Canadian daycare centre collected over a 16-month period by participating in theory/practice inquiry meetings and individual educator interviews. Educators develop an individual understanding of their job’s requirements, individual beliefs and values but also acquire a shared understanding as they collaboratively craft their work in daily informal discussions. Explicit collaborative job crafting could contribute to professional development and improved job satisfaction for Early Childhood Education and Care practitioners. To develop an explicit collaborative understanding of their profession co-workers and supervisors need enabling working conditions such as opportunities and support for professional knowledge sharing, professional reflection, continuous training, and therefore ongoing professional development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".