METI Volume Highlights Education
Bibliographic record
Abstract
Consider this picture: A sandy courtyard some- where on the outskirts of a desert village. A group of boys—ages perhaps 8 to 16—are gathered outside the entrance to a simple, well-worn little building. They are seated or kneeling in the sand, huddled in the last vestiges of the late morning shade. Each holds a text or a tablet. Some are reading, some are looking out to where the pale sky meets a broken line of housetops and trees, reciting, in a quiet murmur to themselves, the words of the book they are holding. Some gently rock back and forth as they read, letting the cadence of their movement compliment the rhythm of the words on the page. Others are writing on tablets of slate or wood. These writers are likewise engaged in the exercise of recitation, but with the pen, setting down line after line from memory. One boy uncrosses his legs, stands up, and steps toward a man who is seated on a little chair in front of the group. As the boy steps forward, his teacher rises and the boy presents his tablet to him. It is written front and back in neat lines of Arabic. Both the teacher and the boy are careful not to smudge the words on the slate. They are sacred words, revealed to a prophet named Muhammad long ago in Mecca, a town on the western edge of Arabia, toward which they have both been praying every day since they were very young.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.658 | 0.355 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".