Historicizing the Knowledge Commons: Open Access, Technical Knowledge, and the Industrial Application of Science
Bibliographic record
Abstract
How does open access relate to scholarly communication? Though there are many modern definitions stressing the accessibility of knowledge to everyone, sharing scientific knowledge has a much longer history. What might the concept of ‘open access’ have meant to scientists and knowledge practitioners over the past several hundred years? This paper poses some relevant questions and calls for better historicization of the idea of the knowledge commons at different periods of time, particularly the era of the ‘Republic of Letters’ and the ‘Modern System of Science.’ The concept of open access as it relates to academic publishing has been very nuanced, and hopefully, understanding the history of ‘open access’ in relation to scholarly communication can help us to have more informed debates about where open access needs to go in the future.
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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 | 0.017 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.012 | 0.017 |
| Science and technology studies | 0.008 | 0.061 |
| Scholarly communication | 0.023 | 0.046 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".