Bibliographic record
Abstract
Our article centres on the question in the sense in which it may be possible to speak of global knowledge, in the first instance. Is it the necessary outcome and the intellectual mark of an age of globalising knowledge societies or is the global demand for the dissemination of knowledge systems trying to answer universally perceived problems? What changes occur to knowledge as it travels and for whom does its globalisation yield benefit or harm? Knowledge must be differentiated from mere information and its locally embedded nature poses serious challenges to opportunities and obstacles for its horizontal and vertical dissemination. Further, global worlds of knowledge raise questions over the ownership of knowledge. Intellectual property claims should be discussed with reference to opposing views, such as those concerning the thesis of knowledge's self‐protective character. Some political and certain idealistic conceptions regard knowledge as common property par excellence. While trade in services and products as well as the digital communications revolution are identified as major vehicles for the dissemination of knowledge, it is yet an open question as to whether they will result in the unhindered dissemination of knowledge or in concentrating it. The second section of the article overviews and introduces the articles in this volume.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.014 |
| Scholarly communication | 0.009 | 0.015 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".