Bibliographic record
Abstract
Darren O’Donnell (b. 1965) is a writer, director, actor, playwright, and designer, and the artistic director of the highly decorated Mammalian Diving Reflex. My study is focused on his work in social acupuncture, outlined in his Social Acupuncture: A guide to suicide, performance, and utopia (2006). Social acupuncture is a style of theatre/performance art that “blurs the line between art and life,”impelling people to come together in unusual ways and tap into the power of the social sphere. With social acupuncture, O’Donnell and Mammalian Diving Reflex are striving to create an aesthetic of civic engagement: an avenue through which social edifices like public space, schools, and the media can be used as the armature for the mounting of work that “takes modest glances at simple power dynamics and, for a moment, provides a glimpse of other possibilities.” Mammalian Diving Reflex began their exploration of the form in the summer of 2003 with The Talking Creature, and since then have devised and performed almost two‐ dozen similar “needles” worldwide.Social acupuncture warrants examination not only from a socio‐ political perspective, but through a theatrical lens, as well. It probes the relationship between audience and performer, raises questions about theatre’s ability to keep up with other media in the digital age, and offers tremendous insight into the potential for positive, fruitful intersections between art and civil society. My project will include theoretical examination of O’Donnell’s work, as well as practical exploration of the form’s potential.
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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.020 | 0.039 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.006 | 0.016 |
| Insufficient payload (model declined to judge) | 0.005 | 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".