Bibliographic record
Abstract
In this paper we argue that by using our bodies we can reflect on our thinking about legal concepts and tools, such as the notion of equality.We consider the ways in which our understanding of equality can be enhanced by re-imagining equality through the medium of physical performance.We also offer an articulation of how we tried to operationalise this more embodied approach to equality, exploring our collaborative experience of trying to present, in a conference setting, the impact of law upon the body, through physical theatre rather than the usual format of oral presentation of written work.In so doing, we reflect upon the experience of standing before an academic audience and using our bodies to enter into dialogue about contemporary debates on equality, with particular attention to this mode of engagement as feminist methodology and feminist critique.Our broader reflections about what we have learned through this project are tied to an understanding of the dynamism of both equality and inequality, and the acknowledgment that substantive learning can result by pushing our own comfort levels as to what is, and what should properly be, the subject, the object and the method of legal knowledge.
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 | 0.018 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.129 |
| Scholarly communication | 0.019 | 0.028 |
| Open science | 0.003 | 0.022 |
| Research integrity | 0.006 | 0.009 |
| 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".