Encounters with Materials in Early Childhood Education
Bibliographic record
Abstract
Encounters with Materials in Early Childhood Education rearticulates understandings of materials—blocks of clay, sheets of paper, brushes and paints—to formulate what happens when we think with materials and apply them to early childhood development and classrooms. The book develops ways of thinking about materials that are more sustainable and insightful than what most children in the Western world experience today through capitalist narratives. Through a series of ethnographic events and engagement with existing ideas of relationality in the visual arts, feminist ethics, science studies, philosophy, and anthropology, Encounters with Materials in Early Childhood Education highlights how materials can be conceptualized as active participants in early childhood education and generators of human insight. A variety of examples show how educators, young children, and researchers have engaged in thinking with materials in early years classrooms and explore what materials are capable of in their encounters with other materials and with children. Please visit the companion website at www.encounterswithmaterials.com for additional features, including interviews with the authors and the teachers featured in the book, videos and photographs of the classroom narratives described in these pages, and an ongoing blog of the authors’ ethnographic notes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".