Transformations: A Personal History of Introducing Complicité into Academic Life and Learning Communities
Bibliographic record
Abstract
This essay documents my three-decade-long journey of connections and resultant transformations between scholarly knowledge and artistic production in my work. In reinvestigating my history with stage and visual arts, I trace the relationship between traditionally ‘alien’ practices and academic understandings of societal and political mass violence and invite the reader to reconsider what academia stands for in order to engage with borderless histories of conflict, violence, and displacement. This essay dwells on how artistic engagement is both a personal and a profoundly political process through which the experience of violence is communicated through thoughts, emotions, hopes, and expressions of trauma. There are also significant ethical concerns present concerning the portrayal of violence, death, and suffering, which the paper discusses under the aegis of ethics of witnessing as responsibility.
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 | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.032 | 0.079 |
| Scholarly communication | 0.021 | 0.015 |
| Open science | 0.002 | 0.026 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.009 | 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".