Open Access Goals Revisited: How Green and Gold Open Access Are Meeting (or Not) Their Original Goals
Bibliographic record
Abstract
The authors ask how far the open access movement has come in meeting its initial goal of making scholarly research freely available to all potential users immediately upon publication through open digital repositories (green OA) or open access journals (gold OA). In 2002, the Budapest Open Access Initiative named the movement and examined the new opportunities that technology made possible. In 2012, the same group declared partial success: ‘We're solidly in the middle.’ The main challenge has been economic sustainability. The authors argue that gold OA has fared better and has more potential for economic stability than green OA. As commercial publishers have found ways to live with and even profit from open access, the movement has not yet achieved its goal of reducing costs for libraries. The future remains uncertain for OA as the means to meeting its goals need more critical evaluation and revision.
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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 | 0.079 | 0.147 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.016 | 0.097 |
| Scholarly communication | 0.057 | 0.072 |
| Open science | 0.005 | 0.033 |
| Research integrity | 0.027 | 0.029 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".