Bibliographic record
Abstract
This article reads the educational implications of ‘intellectual property’ that are found in the double meaning of property, as the word refers to an economic right and a quality of being. It briefly visits the seventeenth-century origins of this double concept of intellectual property (IP), with particular attention paid to John Locke (who provides the basis of IP as a personal possession as well as furthering the idea of a ‘common-wealth of learning’) and the emergence of ‘open science’. The argument proceeds on two levels, educational and public, as it draws parallels between the way that students are taught to regard learning and the way in which a knowledge-based global economy treats learning. On the first level, that of the personal, the article puts forward a critique of the common educational tendency to treat learning as a private good, in terms of personal asset management, which ultimately undermines the common-wealth of learning and the idea of knowledge as a public good. On the second level, that of the public sphere, the article turns to the increasing privatization and capitalization of knowledge that is making inroads into the common-wealth of learning, particularly around publicly funded research and scholarship. The article considers the prospects, finally, of ‘open’ responses (e.g. open access, open source, etc.) to reassert the vital role of the common-wealth, through new technologies of knowledge sharing, and it considers the educational policy implications of preparing a new generation of students who, as they are prepared to participate in knowledge-based economies, should also understand the implications of sustaining the common-wealth of learning.
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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.047 |
| Scholarly communication | 0.014 | 0.016 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".