Bibliographic record
Abstract
<div class="page" title="Page 1"><div class="section"><div class="layoutArea"><div class="column"><p><span>In this article, we respond to Fleer’s (2003) challenge for the need to continue to critically examine the discourses, the codes of practice, the theoretical perspectives and conceptual lenses of early childhood and “question what we have inherited, the histories that we re-enact with each generation of early childhood teachers, and to deconstruct the ‘taken-for-granted’ practices that plague our field” (p. 65). Although we are drawing on Fleer’s scholarly writing from more than 10 years ago, this special issue of the journal suggests that critical examination is ongoing and remains important at the forefront of our work in the early childhood field. Our focus is the environment, the space for play in early childhood education. Rather than add to the numerous de nitions of play, this article aims to offer place as a conceptual lens through which to consider the early play environment, and exemplifes alternative possibilities when researching and/or teaching and learning with children, their families, and the community. </span></p></div></div></div></div>
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.027 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.001 | 0.019 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".