The historian is present: live interactive documentary as collaborative history
Bibliographic record
Abstract
Historical narratives seek to give us a shared reality, argued through recourse to evidence. Both impulses are under threat in the Age of the Anthropocene. This article introduces Live Interactive Documentary, a ‘performance dissemination’ model for history that deploys digital tools to merge cinema and lecture into a new form. It is designed to respond to Hayden White’s challenge in ‘The Burden of History’ and Bruno Latour’s call to gather as a bulwark to misinformation and the manipulative, political cooption of postmodern scepticism. Live Interactive Documentary creates a spectacle of archive and expertise, injected with post-postmodern values of polyphony and audience exchange, grounded in the local. This essay describes the form that I piloted with a team that includes historian Robert Nelson and composer, musician and media artist Brent Lee. Live Interactive Documentary is a model of ‘moving (image) history’ that seeks to cross boundaries between practice and theory, as well as history, film, multimedia performance art and participation. This hybrid cinema model draws upon theories of historiography, film and new media. It digitises earlier models of theatre and film exhibition and responds to the challenges of the Anthropocene by prioritising negotiation, complexity and gathering face-to-face in the real space of our analogue world.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.032 |
| Scholarly communication | 0.020 | 0.021 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 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".