Bibliographic record
Abstract
Abstract Education now functions in an open informational world in which there are essentially no boundaries constraining the information that may be brought to bear on any topic, question, or activity. Changes in the form and connectedness of information are giving rise to new issues concerning coherence, sustained work with ideas, and complexity. In place of the extended text of a well‐crafted book, with its carefully developed line of thought, information on the web is frequently presented as hypertext —relatively small packets of information complexly interlinked. It is now up to the reader to construct a connecting line of thought. The ability to produce coherent knowledge out of such fragmentary information now has a name: transliteracy. Transliteracy requires not only skill in using new information media but ability to carry on sustained integrative work with ideas—an ability traditionally the mark of a skilled teacher but now increasingly the shared capacity of a knowledge‐building community. Whereas traditionally the skilled teacher has smoothed the way to learning by simplifying complex content and problems, functioning in the open informational world requires that learners be able and willing to work with complexity and with problems that have not been structured for them. A current trend is to bring these requirements together in a focus on the “big ideas” of the disciplines. A number of “constructivist” educational approaches engage students in creative knowledge work and problem solving but neglect the sine qua non of contemporary knowledge building: students taking collective responsibility for idea development and improvement.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.021 | 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".