Open sesame: Analysing Public Library of Science as a site of production and distribution for open access scientific information and knowledge
Bibliographic record
Abstract
This article explores the Public Library of Science as a site that produces and disseminates open access scientific information and knowledge for the public good. Through this case study, issues of property ownership, the nature and political economy of biological information, scientific expertise and accessibility of information and scientific knowledge as a public good are considered. Drawing on a cultural industries perspective, I examine the various intermediaries and institutional arrangements that continue to impact and shape the production and dissemination of this open access knowledge. I suggest that Public Library of Science embodies a new mode for the social production of scholarly knowledge and its dissemination, with important implications for how scientific knowledge and expertise are created, certified and circulated.
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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 | 0.008 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.024 | 0.030 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".