Looking into Early Childhood Education and Development Spaces: Visual Ethnography's Contribution to Thinking about Quality
Bibliographic record
Abstract
Discussions about what constitutes a quality early childhood (EC) environment rarely focus on visual or spatial aspects, except to provide background information for talking about EC practice and children's development in the preschool years. There is a need to look beyond the usual quality indicators, which tend to focus on poverty and children's developmental potential so that context and cultural dimensions are often omitted in the discussion. This article thus explores the contribution of visual ethnography for thinking more about, or rethinking, some of the prevailing notions of quality in early childhood education (ECE). To do so, culture is seen as central to the discussion. This includes the organisation of space and the use of materials in EC settings. The idea in this article is to present images that stand in contrast to some of the current globalising discourse about what is good for the world's children. In so doing, the authors thread together seemingly disparate ideas stemming from the centrality of culture and space theory, to the organisation of space, to the use of materials and to transitions in ECE.
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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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.027 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| 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".