Contextualised, Not Neoliberalised, Approaches to Families in Five Countries: Quality and Practice
Bibliographic record
Abstract
Partnerships with parents in early childhood education and care services are a hallmark of quality education. Educators in Western countries work within a highly regulated environment, where government documents, such as frameworks, standards, and curricula, direct most of their work, time, and energy. Despite this, data from our mixed methods online survey from Australia, Canada, Denmark, Georgia, and Italy revealed a strong resistance to the homogeneity these documents prescribe. For the quantitative data, we used cross-tabulation and descriptive statistics. For the qualitative data, we used deductive thematic analysis using a parent–educator partnership framework. Educators described parents in their service as partners in their child’s education. This included efforts to share information, consult, negotiate, and build partnerships; problem solve; and monitor, report and manage the partnership. The educators talked about the uniqueness of their approaches to parents and families within their contextualised services. They then revealed how these unique features impacted their notions of quality and practice in these services. This will be of interest to policymakers, educators, and teacher educators.
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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 | 0.016 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".