Bibliographic record
Abstract
The open area concept and independent study are recent innovations in a growing number of schools. Like most innovations, there is little theory backing their acceptance. A good, brief overview of the thinking behind the open concept school, as interpreted in this paper, is provided in A Day in the Life: Case Studies of Pupils in Open Plan Schools. The words 'open plan' seem to have a number of interpretations in the literature - from free schools to outdoor education. My concern is with that 'openness' which is based on a large, wall-less space within the school building. Similarly, there are many articles on 'independent study in Education Index; most, however, are about audio-visual,library, and programmed instruction activities, and are not concerned with an independent study environment as developed here. Much of this literature speaks of the concern over group conformity and the need to 'individualize' some aspects of the school program. These programs are concerned with subject content and the training of the student's research techniques. These are useful articles for gaining ideas for setting up programs, but my purpose is to take these theories of learning that large open areas aid the learning process, and that learning is promoted in an independent study situation - and develop them strictly from the viewpoint of the effects of the two different environments on the learning process.
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 | 0.028 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.006 | 0.095 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.001 | 0.017 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".