Bibliographic record
Abstract
\n\t\t\t\t\tFound Found Found Found Found Found was an audiovisual essay produced as a response, in part to Jonas Mekas’s diaristic films (Lost Lost Lost) and as a way of bringing Media theorist Vilem Flusser’s thinking on the technical image into my own diaristic practice from the early 70s to the present, from analog to digital practice. The video has been screened at a number of European Film Festivals Signes de Nuit in Paris and Alternativa, in Belgrade, Serbia, LIFT in Toronto, Canada and the Portuguese Cinematheque in 2018, but most importantly published as part of NECSUS (European Network for Cinema and Media Studies) in 2014. Inside it a time-lapse sequence is included a historic program of Australian Innovative and Experimental Film by Nigel Buesst, Paul Fletcher, Lynsey Martin, Michael Lee, Marie Craven, Chris Knowles, Michael Buckley, Sue McCauley, Neil Taylor, Virginia Hilyard, Steven McIntyre and Marcia Jane plus a found footage film I created WAP (White Australia Policy), using images from Rabbit Proof Fence, We of the Never Never. The essay further references the work of George Kuchar and Mike Hoolboom and the soundtrack contains a paranoid rant from Alex Jones’ Info-wars radio program. The film suggests surveillance, metamorphosed from avant-garde and minimalist cinema, as the ‘new norm’, and witnesses the new stasis that hypermobility institutes globally and the florid thinking it elicits. Where does such practice fit in these contemporary discussions on the audio-visual essay, for a practicing artist who belatedly moved into the academy but attempts to present his arguments visually.\n\t\t\t\t
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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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.703 | 0.432 |
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".