What is Feminist About Open Access?: A Relational Approach to Copyright in the Academy
Bibliographic record
Abstract
In a context of great technological and social change, existing intellectual property regimes such as copyright must contend with parallel forms of ownership and distribution. Proponents of open access question and undermine the paradigm of exclusivity central to traditional copyright law, thereby fundamentally challenging its ownership structures and the publishing practices these support. In this essay, we attempt to show what it is about the open access endeavour that resonates with a feminist theory of law and society - in other words, we consider what is “feminist” about open access. First, we provide an overview of a relational feminist critique of traditional copyright law and the assumptions of possessive individualism that pervade it. We then offer a brief description of the open access movement and the way in which it reflects or responds to this criticism. In doing so, we discover vital synergies between this branch of feminist legal theory and the open access movement. Ultimately, we hope to underscore the importance of an open access policy for legal journals such as this one, whose mission is to support, advance and disseminate a feminist perspective that challenges the prevailing hegemony within traditional legal scholarship. We conclude by offering ways in which this journal can help draw out the synergies between feminist criticism and the open access movement.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.068 |
| Scholarly communication | 0.013 | 0.016 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".