Bibliographic record
Abstract
In cities and towns across the United States early childhoodeducators file into college classrooms or hotel conferencerooms and passively take a seat in one of the ordered rowswhere they remain through the day. They come for continu-ing education and training meant to improve their skills and practices in the preschool classroom. Some presenters give PowerPoint presentations; others rely on overhead projectors, slide projectors, or video presentations. Everyone has handouts. Ironically, many of these very workshops and courses focus on how to create interactive, interesting, and purposeful environ-ments in which young children can thrive, not simply survive. We know that carefully designed environments support children’s exploration and learning. Yet the physical environ-ments in which teachers are expected to learn are typically anything but carefully designed. We encounter cold metal chairs in stark rooms, possibly a chalkboard, but seldom a window. Although referred to as “participants, ” teachers in these work-shops often do no more than listen and look.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.019 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.049 | 0.010 |
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".